Combinatorial Approach for Large-scale Identification of Linked Peptides from Tandem Mass Spectrometry Spectra

The combination of chemical cross-linking and mass spectrometry has recently been shown to constitute a powerful tool for studying protein–protein interactions and elucidating the structure of large protein complexes. However, computational methods for interpreting the complex MS/MS spectra from linked peptides are still in their infancy, making the high-throughput application of this approach largely impractical. Because of the lack of large annotated datasets, most current approaches do not capture the specific fragmentation patterns of linked peptides and therefore are not optimal for the identification of cross-linked peptides. Here we propose a generic approach to address this problem and demonstrate it using disulfide-bridged peptide libraries to (i) efficiently generate large mass spectral reference data for linked peptides at a low cost and (ii) automatically train an algorithm that can efficiently and accurately identify linked peptides from MS/MS spectra. We show that using this approach we were able to identify thousands of MS/MS spectra from disulfide-bridged peptides through comparison with proteome-scale sequence databases and significantly improve the sensitivity of cross-linked peptide identification. This allowed us to identify 60% more direct pairwise interactions between the protein subunits in the 20S proteasome complex than existing tools on cross-linking studies of the proteasome complexes. The basic framework of this approach and the MS/MS reference dataset generated should be valuable resources for the future development of new tools for the identification of linked peptides.The study of protein–protein interactions is crucial to understanding how cellular systems function because proteins act in concert through a highly organized set of interactions. Most cellular processes are carried out by large macromolecular assemblies and regulated through complex cascades of transient protein–protein interactions (1). In the past several years numerous high-throughput studies have pioneered the systematic characterization of protein–protein interactions in model organisms (2–4). Such studies mainly utilize two techniques: the yeast two-hybrid system, which aims at identifying binary interactions (5), and affinity purification combined with tandem mass spectrometry analysis for the identification of multi-protein assemblies (6–8). Together these led to a rapid expansion of known protein–protein interactions in human and other model organisms. Patche and Aloy recently estimated that there are more than one million interactions catalogued to date (9).But despite rapid progress, most current techniques allow one to determine only whether proteins interact, which is only the first step toward understanding how proteins interact. A more complete picture comes from characterizing the three-dimensional structures of protein complexes, which provide mechanistic insights that govern how interactions occur and the high specificity observed inside the cell. Traditionally the gold-standard methods used to solve protein structures are x-ray crystallography and NMR, and there have been several efforts similar to structural genomics (10) aiming to comprehensively solve the structures of protein complexes (11, 12). Although there has been accelerated growth of structures for protein monomers in the Protein Data Bank in recent years (11), the growth of structures for protein complexes has remained relatively small (9). Many factors, including their large size, transient nature, and dynamics of interactions, have prevented many complexes from being solved via traditional approaches in structural biology. Thus, the development of complementary analytical techniques with which to probe the structure of large protein complexes continues to evolve (13–18).Recent developments have advanced the analysis of protein structures and interaction by combining cross-linking and tandem mass spectrometry (17, 19–24). The basic idea behind this technique is to capture and identify pairs of amino acid residues that are spatially close to each other. When these linked pairs of residues are from the same protein (intraprotein cross-links), they provide distance constraints that help one infer the possible conformations of protein structures. Conversely, when pairs of residues come from different proteins (interprotein cross-links), they provide information about how proteins interact with one another. Although cross-linking strategies date back almost a decade (25, 26), difficulty in analyzing the complex MS/MS spectrum generated from linked peptides made this approach challenging, and therefore it was not widely used. With recent advances in mass spectrometry instrumentation, there has been renewed interest in employing this strategy to determine protein structures and identify protein–protein interactions. However, most studies thus far have been focused on purified protein complexes. With today''s mass spectrometers being capable of analyzing tens of thousands of spectra in a single experiment, it is now potentially feasible to extend this approach to the analysis of complex biological samples. Researchers have tried to realize this goal using both experimental and computational approaches. Indeed, a plethora of chemical cross-linking reagents are now available for stabilizing these complexes, and some are designed to allow for easier peptide identification when employed in concert with MS analysis (20, 27, 28). There have also been several recent efforts to develop computational methods for the automatic identification of linked peptides from MS/MS spectra (29–36). However, because of the lack of large annotated training data, most approaches to date either borrow fragmentation models learned from unlinked, linear peptides or learn the fragmentation statistics from training data of limited size (30, 37), which might not generalize well across different samples. In some cases it is possible to generate relatively large training data, but it is often very labor intensive and involves hundreds of separate LC-MS/MS runs (36). Here, employing disulfide-bridged peptides as an example, we propose a novel method that uses a combinatorial peptide library to (a) efficiently generate a large mass spectral reference dataset for linked peptides and (b) use these data to automatically train our new algorithm, MXDB, which can efficiently and accurately identify linked peptides from MS/MS spectra.     

Mass Spectrometry Imaging and Identification of Peptides Associated with Cephalic Ganglia Regeneration in Schmidtea mediterranea

Tissue regeneration is a complex process that involves a mosaic of molecules that vary spatially and temporally. Insights into the chemical signaling underlying this process can be achieved with a multiplex and untargeted chemical imaging method such as mass spectrometry imaging (MSI), which can enable de novo studies of nervous system regeneration. A combination of MSI and multivariate statistics was used to differentiate peptide dynamics in the freshwater planarian flatworm Schmidtea mediterranea at different time points during cephalic ganglia regeneration. A protocol was developed to make S. mediterranea tissues amenable for MSI. MS ion images of planarian tissue sections allow changes in peptides and unknown compounds to be followed as a function of cephalic ganglia regeneration. In conjunction with fluorescence imaging, our results suggest that even though the cephalic ganglia structure is visible after 6 days of regeneration, the original chemical composition of these regenerated structures is regained only after 12 days. Differences were observed in many peptides, such as those derived from secreted peptide 4 and EYE53-1. Peptidomic analysis further identified multiple peptides from various known prohormones, histone proteins, and DNA- and RNA-binding proteins as being associated with the regeneration process. Mass spectrometry data also facilitated the identification of a new prohormone, which we have named secreted peptide prohormone 20 (SPP-20), and is up-regulated during regeneration in planarians.     

Identification of Antibacterial Phenolics in Selected Plant Species from Mexican Cloud Forest by Mass Spectrometry Dereplication

Fifteen plant species from a protected cloud forest (CF) in Veracruz, Mexico, were screened for their in vitro capacity to inhibit the growth of the phytopathogenic bacteria Chryseobacterium sp., Pseudomonas cichorii, Pectobacterium carotovorum and Pantoea stewartii, causal agents of damage to crops like ‘chayote’, lettuce, potato and corn. As a result, the bioactivity of Turpinia insignis and Leandra cornoides is reported for the first time against Chryseobacterium sp. and P. cichorii. In addition, 24 and 18 compounds not described for these species were dereplicated by an UPLC/MS‐MS method, respectively. The identified compounds included simple phenols, hydroxycinnamic acids, flavonoids and coumarins. The antibacterial assay of 12 of them demonstrated the bacteriostatic effect of vanillin, trans‐cinnamic acid, scopoletin and umbelliferone against Chryseobacterium sp. These findings confirm for the first time the value of the CF plants from Veracruz as sources of bioactive natural products with antimicrobial properties against phytopathogenic bacteria.     

Identification and Monitoring of Host Cell Proteins by Mass Spectrometry Combined with High Performance Immunochemistry Testing

Biotherapeutics are often produced in non-human host cells like Escherichia coli, yeast, and various mammalian cell lines. A major focus of any therapeutic protein purification process is to reduce host cell proteins to an acceptable low level. In this study, various E. coli host cell proteins were identified at different purifications steps by HPLC fractionation, SDS-PAGE analysis, and tryptic peptide mapping combined with online liquid chromatography mass spectrometry (LC-MS). However, no host cell proteins could be verified by direct LC-MS analysis of final drug substance material. In contrast, the application of affinity enrichment chromatography prior to comprehensive LC-MS was adequate to identify several low abundant host cell proteins at the final drug substance level. Bacterial alkaline phosphatase (BAP) was identified as being the most abundant host cell protein at several purification steps. Thus, we firstly established two different assays for enzymatic and immunological BAP monitoring using the cobas® technology. By using this strategy we were able to demonstrate an almost complete removal of BAP enzymatic activity by the established therapeutic protein purification process. In summary, the impact of fermentation, purification, and formulation conditions on host cell protein removal and biological activity can be conducted by monitoring process-specific host cell proteins in a GMP-compatible and high-throughput (> 1000 samples/day) manner.     

Characterization of Hydrophobic Peptides in the Presence of Detergent by Photoionization Mass Spectrometry

The characterization of membrane proteins is still challenging. The major issue is the high hydrophobicity of membrane proteins that necessitates the use of detergents for their extraction and solubilization. The very poor compatibility of mass spectrometry with detergents remains a tremendous obstacle in studies of membrane proteins. Here, we investigated the potential of atmospheric pressure photoionization (APPI) for mass spectrometry study of membrane proteins. This work was focused on the tetraspanin CD9 and the multidrug transporter BmrA. A set of peptides from CD9, exhibiting a broad range of hydropathicity, was investigated using APPI as compared to electrospray ionization (ESI). Mass spectrometry experiments revealed that the most hydrophobic peptides were hardly ionized by ESI whereas all peptides, including the highly hydrophobic one that corresponds to the full sequence of the first transmembrane domain of CD9, were easily ionized by APPI. The native protein BmrA purified in the presence of the non-ionic detergent beta-D-dodecyl maltoside (DDM) was digested in-solution using trypsin. The resulting peptides were investigated by flow injection analysis of the mixture followed by mass spectrometry. Upon ESI, only detergent ions were detected and the ionic signals from the peptides were totally suppressed. In contrast, APPI allowed many peptides distributed along the sequence of the protein to be detected. Furthermore, the parent ion corresponding to the first transmembrane domain of the protein BmrA was detected under APPI conditions. Careful examination of the APPI mass spectrum revealed a-, b-, c- and y- fragment ions generated by in-source fragmentation. Those fragment ions allowed unambiguous structural characterization of the transmembrane domain. In conclusion, APPI–MS appears as a versatile method allowing the ionization and fragmentation of hydrophobic peptides in the presence of detergent.     

液质联用多反应监测法定量目标多肽或蛋白质

为建立优化的血浆内源性多肽提取方法,并且构建目标多肽和蛋白质的质谱定量方 法,本研究考察了超滤法、有机溶剂沉淀法和固相萃取法对血浆内源性多肽的提取效果 ,并通过Tricine-SDS-PAGE对提取效果进行比较.通过液相色谱串联质谱多反应监测 （MRM）分析,建立了多肽标准品ESAT-6定量方法,并将ESAT-6定量建立的液相色谱和质谱条件应用于蛋白质的定量,对多肽和蛋白质MRM定量的标准曲线进行了考 察.Tricine-SDS-PAGE结果表明,乙腈沉淀法是最佳的血浆内源性多肽提取方法,低分子量的多肽可以得到很好的富集,且能有效地去除高分子蛋白质的污染.液相色谱串联 质谱MRM法检测血浆内提取的多肽,标准曲线的线性较好,相关系数为0.999.另外,采 用MRM法对胶内分离的蛋白质进行定量,标准曲线的线性相关系数为0.995.综上所述, 本研究构建了一种简单有效的血浆多肽提取方法,通过液质联用MRM法成功地实现了目标多肽和蛋白质定量测定.该定量方法可以推广应用于复杂样品中的多肽和蛋白质的定 量分析.     

Identification of a Major Phosphopeptide in Human Tristetraprolin by Phosphopeptide Mapping and Mass Spectrometry

Tristetraprolin/zinc finger protein 36 (TTP/ZFP36) binds and destabilizes some pro-inflammatory cytokine mRNAs. TTP-deficient mice develop a profound inflammatory syndrome due to excessive production of pro-inflammatory cytokines. TTP expression is induced by various factors including insulin and extracts from cinnamon and green tea. TTP is highly phosphorylated in vivo and is a substrate for several protein kinases. Multiple phosphorylation sites are identified in human TTP, but it is difficult to assign major vs. minor phosphorylation sites. This study aimed to generate additional information on TTP phosphorylation using phosphopeptide mapping and mass spectrometry (MS). Wild-type and site-directed mutant TTP proteins were expressed in transfected human cells followed by in vivo radiolabeling with [³²P]-orthophosphate. Histidine-tagged TTP proteins were purified with Ni-NTA affinity beads and digested with trypsin and lysyl endopeptidase. The digested peptides were separated by C₁₈ column with high performance liquid chromatography. Wild-type and all mutant TTP proteins were localized in the cytosol, phosphorylated extensively in vivo and capable of binding to ARE-containing RNA probes. Mutant TTP with S⁹⁰ and S⁹³ mutations resulted in the disappearance of a major phosphopeptide peak. Mutant TTP with an S¹⁹⁷ mutation resulted in another major phosphopeptide peak being eluted earlier than the wild-type. Additional mutations at S¹⁸⁶, S²⁹⁶ and T²⁷¹ exhibited little effect on phosphopeptide profiles. MS analysis identified the peptide that was missing in the S⁹⁰ and S⁹³ mutant protein as LGPELSPSPTSPTATSTTPSR (corresponding to amino acid residues 83–103 of human TTP). MS also identified a major phosphopeptide associated with the first zinc-finger region. These analyses suggest that the tryptic peptide containing S⁹⁰ and S⁹³ is a major phosphopeptide in human TTP.     

Identification of Abscisic Acid in Tulipa gesneriana L. by Gas-Liquid Chromatography with Electron Capture and Combined Gas-Liquid Chromatography and Mass Spectrometry

A major growth inhibitory substance of tulip bulbs (Tulipa gesneriana L. cv Paul Richter) has been unequivocally shown to be abscisic acid (ABA). The ABA methyl ester of the free ether-soluble acid fractions of tulip organs had the identical retention time on gas-liquid chromatography with electron capture detector as authentic ABA methyl ester. In addition, the mass spectra were the same. On a unit dry matter basis, the basalplate and floral shoot contained 3.6 and 2.6 times more ABA than the fleshy scales, respectively.     

Identification of the Phosphorylated Residues in TveIF5A by Mass Spectrometry

The initiation factor elF5A in Trichomonas vaginalis （TvelF5A） is previously shown to undergo hypusination, phosphorylation and glycosylation. Three different pI isoforms of TvelF5A have been reported. The most acidic isoform （pI 5.2） corresponds to the precursor TvelF5A, whereas the mature TvelF5A appears to be the most basic isoform （pI 5.5）. In addition, the intermediary isoform （pI 5.3） is found only under polyamine-depleted conditions and restored with exogenous putrescine. We propose that differences in PI are due to phosphorylation of the TvelF5A isoforms. Here, we have identified phosphorylation sites using mass spectrometry. The mature TvelF5A contains four phosphorylated residues （$3, T55, T78 and T82）. Phosphorylation at $3 and T82 is also identified in the intermediary TvelF5A, while no phosphorylated residues are found in the precursor TvelF5A. It has been demonstrated that elF5A proteins from plants and yeast are phosphorylated by a casein kinase 2 （CK2）. Interestingly, a gene encoding a protein highly similar to CK2 （TvCK2） is found in T. vaginalis, which might be involved in the phosphorylation of TvelF5A in T. vaginalis.     

Identification of Microalgae by Laser Desorption/Ionization Mass Spectrometry Coupled with Multiple Nanomatrices

In this study, we demonstrate a simple method to identify microalgae by surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS) using three different substrates: HgSe, HgTe, and HgTeSe nanostructures. The fragmentation/ionization processes of complex molecules in algae varied according to the heat absorption and transfer efficiency of the nanostructured matrices (NMs). Therefore, the mass spectra obtained for microalgae showed different patterns of m/z values for different NMs. The spectra contained both significant and nonsignificant peaks. Constructing a Venn diagram with the significant peaks obtained for algae when using HgSe, HgTe, and HgTeSe NMs in m/z ratio range 100–1000, a unique relationship among the three sets of values was obtained. This unique relationship of sets is different for each species of microalgae. Therefore, by observing the particular relationship of sets, we successfully identified different algae such as Isochrysis galbana, Emiliania huxleyi, Thalassiosira weissflogii, Nannochloris sp., Skeletonema cf. costatum, and Tetraselmis chui. This simple and cost-effective SALDI-MS analysis method coupled with multi-nanomaterials as substrates may be extended to identify other microalgae and microorganisms in real samples.

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Graphical Abstract Identification of microalgae by surface-assisted laser desorption/ionization mass spectrometry coupled with three different mercury-based nanosubstrates

     

Nucleic Acids in Protein Samples Interfere with Phosphopeptide Identification by Immobilized-Metal-Ion Affinity Chromatography and Mass Spectrometry

Immobilized-metal-ion affinity chromatography (IMAC) is used extensively for phosphopeptide enrichment in phosphoproteomics. However, the effect of nucleic acids in protein samples on phosphopeptide enrichment by IMAC has not yet been well clarified. In this study, we demonstrate that IMAC beads possess a strong adsorption of nucleic acids, especially single-stranded or single-stranded-region-containing nucleic acids, leading to approximately 50% loss of phosphopeptides during the process of IMAC enrichment. Therefore, nucleic acids must be removed from protein samples prior to IMAC. Acetonitrile (ACN) precipitation, a simple and efficient procedure, was established to remove nucleic acids from the protein samples. We showed that ACN precipitation approximately doubled the phosphopeptide number identified by IMAC and mass spectrometry, indicating that nucleic acid removal significantly improves the identification of phosphopeptides. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A Combined Laser Microdissection and Mass Spectrometry Approach Reveals New Disease Relevant Proteins Accumulating in Aggregates of Filaminopathy Patients

Filaminopathy is a subtype of myofibrillar myopathy caused by mutations in FLNC, the gene encoding filamin C, and histologically characterized by pathologic accumulation of several proteins within skeletal muscle fibers. With the aim to get new insights in aggregate composition, we collected aggregates and control tissue from skeletal muscle biopsies of six myofibrillar myopathy patients harboring three different FLNC mutations by laser microdissection and analyzed the samples by a label-free mass spectrometry approach. A total of 390 proteins were identified, and 31 of those showed significantly higher spectral indices in aggregates compared with patient controls with a ratio >1.8. These proteins included filamin C, other known myofibrillar myopathy associated proteins, and a striking number of filamin C binding partners. Across the patients the patterns were extremely homogeneous. Xin actin-binding repeat containing protein 2, heat shock protein 27, nebulin-related-anchoring protein, and Rab35 could be verified as new filaminopathy biomarker candidates. In addition, further experiments identified heat shock protein 27 and Xin actin-binding repeat containing protein 2 as novel filamin C interaction partners and we could show that Xin actin-binding repeat containing protein 2 and the known interaction partner Xin actin-binding repeat containing protein 1 simultaneously associate with filamin C. Ten proteins showed significant lower spectral indices in aggregate samples compared with patient controls (ratio <0.56) including M-band proteins myomesin-1 and myomesin-2. Proteomic findings were consistent with previous and novel immunolocalization data. Our findings suggest that aggregates in filaminopathy have a largely organized structure of proteins also interacting under physiological conditions. Different filamin C mutations seem to lead to almost identical aggregate compositions. The finding that filamin C was detected as highly abundant protein in aggregates in filaminopathy indicates that our proteomic approach may be suitable to identify new candidate genes among the many MFM patients with so far unknown mutation.Myofibrillar myopathies (MFM)¹ encompass a genetic and clinically heterogenous group of muscle disorders characterized by focal myofibrillar destruction and massive protein aggregation within skeletal muscle fibers (1). The mechanisms leading to aggregate formation are not well understood but an impairment of protein degradation systems seems to play an important role (2). Immunohistochemical studies identified various proteins accumulating in these aggregates (3) but the precise composition is unknown so far. The latter may give us important new insights in the pathogenesis of MFM.Filaminopathy is a subtype of MFM caused by mutations in the rod domain of FLNC, the gene encoding FLNc (4–7). Filamins are a small group of large cytoskeletal proteins that crosslink F-actin filaments and act as scaffold for transmembrane receptors, signaling, and adapter proteins. FLNc is the striated muscle-specific isoform that cross-links actin at the Z-disc level and is important for the maintenance of myofibrillar integrity. Filaminopathy is leading to a progressive muscle weakness usually manifesting between the fourth and sixth decade of life. The pattern of severely and hardly affected muscles detected by magnetic resonance imaging is very homogeneous across patients with different FLNC mutations (8, 9, and unpublished data). In advanced stages of the disease, patients generally lose the ability to walk and show respiratory insufficiency because of weakness of respiratory muscles. A cardiac involvement is also frequent (4, 5).Over the last years proteomics has developed to a promising tool for the analysis of the skeletal muscle proteome. Several studies including gel-based and mass spectrometric approaches have been performed that mainly aimed at the global cataloguing and biochemical characterization of the whole rodent muscle proteome or of cellular substructures under physiological and aging conditions (10,11, and for review see (12)). In aged muscles, for example, abundance changes have been detected for proteins involved in metabolism, contractile activity, myofibrillar remodeling, and stress response (12). In biomedical research global studies focused on the identification of novel panels of protein biomarker candidates for neuromuscular diseases: Analyses of muscle tissue of the dystrophin deficient mouse model of Duchenne muscular dystrophy (mdx mouse) identified altered levels of protein biomarkers involved in nucleotide metabolism, cellular stress response, energy metabolism, and ion handling (for review see (13)). Significant alterations of proteins playing an important role in various metabolic pathways were found in a mouse model for hypokalemic myopathy (14). In a 2-DE study of total muscle extracts from dysferlinopathy patients, 35 proteins were found to be differentially expressed (15). Metabolic and contractile proteins represented the majority of the changes suggesting an active process of muscle regeneration and a remodeling of fiber type as a result of dysferlin deficiency. In sporadic inclusion body myositis (sIBM), proteins associated with amyloidosis were up-regulated (16). A comparison of protein expression in sIBM to non-IBM inflammatory myopathies indicated an impairment of detoxification, energy metabolism, and protein folding in sIBM (16).All of the above mentioned studies used total muscle protein extracts or soluble cytosolic protein fractions resulting in limitations because of high sample heterogeneity and complexity. Muscle tissue is composed of a complex mixture of different cell types from epi-, endo-, perimysium, muscle spindles, blood vessels etc. and changes in the protein abundance might be the result of differences in sample composition rather than disease-related effects. Additionally, the presence of a number of highly abundant and unusually large proteins (e.g. actin, myosin, titin) hampers the detection of potentially relevant low abundant disease-associated proteins. Those limitations could be bypassed by application of technologies allowing specific isolation of physiologically and pathophysiologically relevant muscular substructures before proteomic analysis, such as (sub) cellular microdissection. This can either be performed manually (17, 18) or laser-assisted, and provides unparalleled accuracy obtaining pure cell populations or even pure subcellular structures (for review see (19)). Laser microdissection (LMD) in combination with mass spectrometry has been successfully applied for reducing body myopathy (RBM) (20), a hereditary muscle disease histologically characterized by intracytoplasmic inclusions, so called reducing bodies. FHL1 (four and a half LIM domain 1) was identified as the most prominent component of isolated reducing bodies. Subsequently performed mutational analysis revealed different pathogenic FHL1 mutations in RBM patients. This was the first example of an essential contribution of a proteomic approach to the identification of the disease-causing mutation in a hereditary myopathy.The aim of our study was to identify proteins that accumulate in protein aggregates within muscle fibers in MFM associated with FLNC mutations in order to get new insights in the pathomechanisms and to detect specific protein biomarker candidates for differential diagnosis. Skeletal muscle biopsies of six patients with three different FLNC mutations have been included in this study. LMD in combination with a newly established label-free mass spectrometry approach reproducibly identified and relatively quantified 390 proteins in total. We were able to detect new components of protein aggregates in filaminopathy and describe and characterize the so far unknown interaction between FLNc and Xin actin-binding repeat containing protein 2 (Xirp2).     

Identification by MALDI-TOF Mass Spectrometry of Mercury-resistant Bacteria Associated with the Rhizosphere of an Apple Orchard

In this work, mercury-resistant bacterial strains were isolated from the rhizosphere of an apple orchard, growing in a soil with high levels of mercury (Nuevo San Joaquin, Queretaro State, Mexico). Analysis of the soil in this region by the Cold Vapor Atomic Absortion Spectroscopy method showed that it contained 637 ± 51 mg mercury per kg. Mercury accumulation by fresh apples from this orchard amounted to 15.44 ± 4.33 mg/kg. The bacterial isolates were identified by application of proteomic technique of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). They were found to be strains of Bacillus muralis and Bacillus simplex. All strains showed the ability to catalyze the volatilization of Hg as measured via the nonradioactive X-ray method. In all strains merR and merA genes were detected by polymerase chain reaction. Nucleotide sequence analysis showed that merR from B. simplex was 435 bp in length and that its sequence was similar to merR sequences reported for other bacteria such as Cupriavidus, Ralstonia, Pseudomonas and Serratia. To our knowledge, this is the first report of mercury-resistant Bacillus strains isolated from the rhizosphere of an apple orchard and the first merR gene sequence from such Bacilli.     

Identification of n-Decane Oxidation Products in Corynebacterium Cultures by Combined Gas Chromatography-Mass Spectrometry

The gas chromatography-mass spectrometry technique was employed to characterize n-decane oxidation products of Corynebacterium strains 7E1C and 269 (SNAM Progetti collection) after 73 h of incubation at 35 C. Corynebacterium 7E1C accumulated consistent amounts of esters of long chain acids with long chain alcohols, mainly decyldecanoate as well as products with mono- and diterminal carboxylic functions. Corynebacterium 269 yielded 1-decanol and 1-10 decanediol as principal oxidation products.     

Identification of 1,4-Benzoxazin-3-ones in Maize Extracts by Gas-Liquid Chromatography and Mass Spectrometry

Gas-liquid chromatography-mass spectrometry (GLC-MS) has been used for the separation, detection, and identification of 1,4-benzoxazin-3-ones (hydroxamic acids and lactams) and benzoxazolinones found in maize (Zea mays L.) extracts. Compounds of interest were partitioned into ethyl acetate from aqueous maize seedling extracts. For analysis by GLC-MS, trimethylsilyl derivatives were prepared, chromatographed on a column of 3% OV-1, and detected in the mass spectrometer. Mass spectra were obtained for all peaks present in extracts of four maize lines. A data comparison system was developed for relating unidentified spectra to the spectra of the reference compounds. Based on spectral comparisons, three hydroxamic acids (2,4-dihydroxy-2H-1, 4-benzoxazin-3(4H)-one; 2,4-dihydroxy-7-methoxy-2H-1,4-benzoxazin-3(4H)-one; and 2,4-dihydroxy-7,8-dimethoxy-2H-1,4-benzoxazin-3(4H)-one), three lactams (2-hydroxy-2H-1,4-benzoxazin-3(4H)-one; 2,7-dihydroxy-2H-1,4-benzoxazin-3(4H)-one; and 2-hydroxy-7-methoxy-2H-1,4-benzoxazin-3(4H)-one), one benzoxazolinone (6-methoxybenzoxazolinone), and two organic acids (malic and aconitic) were identified in the extracts. In addition, one other hydroxamic acid and one other related compound were tentatively identified based on mass spectral evidence.     

Spatial Distribution of Endogenous Tissue Protease Activity in Gastric Carcinoma Mapped by MALDI Mass Spectrometry Imaging

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Highlights

• •New MALDI MS imaging sample preparation workflow reveals tissue protease activity.
• •Differential time- and inhibitor concentration-dependence confirm active proteases.
• •Mouse gastric tumor displays high protease activity compared to surrounding tissue.
• •Proteomic data and biochemical protease activity assay support MALDI MSI results.