IR spectroscopic analyses of amyloid fibril formation of ß2-microglobulin using a simplified procedure for its in vitro generation at neutral pH.

ß2-microglobulin (ß2m) is known to be the major component of fibrillar deposits in the joints of patients suffering from dialysis-related amyloidosis. We have developed a simplified procedure to convert monomeric recombinant ß2m into amyloid fibrils at physiological pH by a combination of stirring and heating, enabling us to follow conformational changes associated with the assembly by infrared spectroscopy and electron microscopy. Our studies reveal that fibrillogenesis begins with the formation of relatively large aggregates, with secondary structure not significantly altered by the stirring-induced association. In contrast, the conversion of the amorphous aggregates into amyloid fibrils is associated with a profound re-organization at the level of the secondary and tertiary structures, leading to non-native like parallel arrangements of the ß-strands in the fully formed amyloid structure of ß2m. This study highlights the power of an approach to investigate the formation of ß2m fibrils by a combination of biophysical techniques including IR spectroscopy.

Genetic diversity of Burkholderia contaminans isolates from cystic fibrosis patients in Argentina.

A total of 120 Burkholderia cepacia complex isolates collected during 2004-2010 from 66 patients in two cystic fibrosis reference centers in Argentina were analyzed. Burkholderia contaminans was the species most frequently recovered (57.6%), followed by Burkholderia cenocepacia (15%), a species distribution not reported so far. The recA-PCR-based techniques applied to the B. contaminans isolates revealed that 85% of the population carried the recA-ST-71 allele. Our results showed the utility of BOX-PCR genotyping in analyzing B. contaminans diversity. This approach allowed us to address clonal transmission during an outbreak and the genetic changes occurring in infecting bacteria over the course of chronic infection.

Identification of the protease cleavage sites in a reconstituted Gag polyprotein of an HERV-K(HML-2) element.

BACKGROUND: The human genome harbors several largely preserved HERV-K(HML-2) elements. Although this retroviral family comes closest of all known HERVs to producing replication competent virions, mutations acquired during their chromosomal residence have rendered them incapable of expressing infectious particles. This also holds true for the HERV-K113 element that has conserved open reading frames (ORFs) for all its proteins in addition to a functional LTR promoter. Uncertainty concerning the localization and impact of post-insertional mutations has greatly hampered the functional characterization of these ancient retroviruses and their proteins. However, analogous to other betaretroviruses, it is known that HERV-K(HML-2) virions undergo a maturation process during or shortly after release from the host cell. During this process, the subdomains of the Gag polyproteins are released by proteolytic cleavage, although the nature of the mature HERV-K(HML-2) Gag proteins and the exact position of the cleavage sites have until now remained unknown. RESULTS: By aligning the amino acid sequences encoded by the gag-pro-pol ORFs of HERV-K113 with the corresponding segments from 10 other well-preserved human specific elements we identified non-synonymous post-insertional mutations that have occurred in this region of the provirus. Reversion of these mutations and a partial codon optimization facilitated the large-scale production of maturation-competent HERV-K113 virus-like particles (VLPs). The Gag subdomains of purified mature VLPs were separated by reversed-phase high-pressure liquid chromatography and initially characterized using specific antibodies. Cleavage sites were identified by mass spectrometry and N-terminal sequencing and confirmed by mutagenesis. Our results indicate that the gag gene product Pr74Gag of HERV-K(HML-2) is processed to yield p15-MA (matrix), SP1 (spacer peptide of 14 amino acids), p15, p27-CA (capsid), p10-NC (nucleocapsid) and two C-terminally encoded glutamine- and proline-rich peptides, QP1 and QP2, spanning 23 and 19 amino acids, respectively. CONCLUSIONS: Expression of reconstituted sequences of original HERV elements is an important tool for studying fundamental aspects of the biology of these ancient viruses. The analysis of HERV-K(HML-2) Gag processing and the nature of the mature Gag proteins presented here will facilitate further studies of the discrete functions of these proteins and of their potential impact on the human host.

Evaluation of tip-enhanced Raman spectroscopy for characterizing different virus strains.

Tip-enhanced Raman spectroscopy (TERS) is a highly sensitive spectroscopic technique which combines the advantages of optical spectroscopy with the requirements needed for the characterization of biological nano-structures. In this study, TERS was used to investigate the applicability of this spectroscopic technique for the detection of different virus strains like avipoxvirus and adeno-associated virus. TERS spectra obtained from different particles of the same virus strain show variations in relative peak intensities and positions of most spectral features observed. These spectral variations were higher for the larger avipoxvirus particles (∅≈350 nm) than for the smaller adeno-associated virus particles (∅≈26 nm).

Rapid identification of Burkholderia cepacia complex species including strains of the novel Taxon K, recovered from cystic fibrosis patients by intact cell MALDI-ToF mass spectrometry.

Two approaches based on intact cell matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (IC-MALDI-ToF MS) have been evaluated in order to discriminate and identify nine former Burkholderia cepacia complex (Bcc) species, Burkholderia contaminans belonging to the novel Taxon K, Burkholderia gladioli, and the most relevant non-fermentative (NF) Gram-negative rods recovered from cystic fibrosis (CF) sputum cultures. In total, 146 clinical isolates and 26 reference strains were analysed. IC mass spectra were obtained with high reproducibility applying a recently developed inactivation protocol which is based on the extraction of microbial proteins by trifluoroacetic acid (TFA). In a first approach, spectral analysis was carried out by means of a gel-view representation of mass spectra, which turned out to be useful to recognize specific identifying biomarker proteins (SIBPs). A series of prominent mass peaks, mainly assigned to constitutively expressed proteins, were selected as SIBPs for identifications at the genus and species level. Two distinctive mass peaks present in B. contaminans spectra (7501 and 7900 Da) were proposed as SIBPs for the identification of this novel species. A second approach of spectral analysis based on data reduction, feature selection and subsequent hierarchical cluster analysis was used to obtain an objective discrimination of all species analysed. Both complementary modalities of analyzing complex IC-MALDI-ToF MS data open the path towards a rapid, accurate and objective means of routine clinical microbiology diagnosis of pathogens from sputum samples of CF patients.

Fourier transform infrared spectroscopy for rapid identification of nonfermenting gram-negative bacteria isolated from sputum samples from cystic fibrosis patients.

The accurate and rapid identification of bacteria isolated from the respiratory tract of patients with cystic fibrosis (CF) is critical in epidemiological studies, during intrahospital outbreaks, for patient treatment, and for determination of therapeutic options. While the most common organisms isolated from sputum samples are Pseudomonas aeruginosa, Staphylococcus aureus, and Haemophilus influenzae, in recent decades an increasing fraction of CF patients has been colonized by other nonfermenting (NF) gram-negative rods, such as Burkholderia cepacia complex (BCC) bacteria, Stenotrophomonas maltophilia, Ralstonia pickettii, Acinetobacter spp., and Achromobacter spp. In the present study, we developed a novel strategy for the rapid identification of NF rods based on Fourier transform infrared spectroscopy (FTIR) in combination with artificial neural networks (ANNs). A total of 15 reference strains and 169 clinical isolates of NF gram-negative bacteria recovered from sputum samples from 150 CF patients were used in this study. The clinical isolates were identified according to the guidelines for clinical microbiology practices for respiratory tract specimens from CF patients; and particularly, BCC bacteria were further identified by recA-based PCR followed by restriction fragment length polymorphism analysis with HaeIII, and their identities were confirmed by recA species-specific PCR. In addition, some strains belonging to genera different from BCC were identified by 16S rRNA gene sequencing. A standardized experimental protocol was established, and an FTIR spectral database containing more than 2,000 infrared spectra was created. The ANN identification system consisted of two hierarchical levels. The top-level network allowed the identification of P. aeruginosa, S. maltophilia, Achromobacter xylosoxidans, Acinetobacter spp., R. pickettii, and BCC bacteria with an identification success rate of 98.1%. The second-level network was developed to differentiate the four most clinically relevant species of BCC, B. cepacia, B. multivorans, B. cenocepacia, and B. stabilis (genomovars I to IV, respectively), with a correct identification rate of 93.8%. Our results demonstrate the high degree of reliability and strong potential of ANN-based FTIR spectrum analysis for the rapid identification of NF rods suitable for use in routine clinical microbiology laboratories.

HLA-B27 subtypes differentially associated with disease exhibit conformational differences in solution.

Human leukocyte antigen (HLA) class I molecules consist of a heavy chain, beta(2)-microglobulin, and a peptide that are noncovalently bound. Certain HLA-B27 subtypes are associated with ankylosing spondylitis (such as HLA-B*2705), whereas others (such as HLA-B*2709) are not. Both differ in only one residue (Asp116 and His116, respectively) in the F pocket that accommodates the peptide C-terminus. An isotope-edited IR spectroscopy study of these HLA-B27 subtypes complexed with the self-peptide RRKWRRWHL was carried out, revealing that the heavy chain is more flexible in the HLA-B*2705 than in the HLA-B*2709 subtype. In agreement with these experimental data, molecular dynamics simulations showed an increased flexibility of the HLA-B*2705 binding groove in comparison with that of the HLA-B*2709 subtype. This difference correlates with an opening of the HLA-B*2705 binding groove, accompanied by a partial detachment of the C-terminal peptide anchor. These combined results demonstrate how the deeply embedded polymorphic heavy-chain residue 116 influences the flexibility of the peptide binding groove in a subtype-dependent manner, a feature that could also influence the recognition of the HLA-B27 complexes by effector cells.

Artificial neural networks as supervised techniques for FT-IR microspectroscopic imaging.

In this report the applicability of an improved method of image segmentation of infrared microspectroscopic data from histological specimens is demonstrated. Fourier transform infrared (FT-IR) microspectroscopy was used to record hyperspectral data sets from human colorectal adenocarcinomas and to build up a database of spatially resolved tissue spectra. This database of colon microspectra comprised 4120 high-quality FT-IR point spectra from 28 patient samples and 12 different histological structures. The spectral information contained in the database was employed to teach and validate multilayer perceptron artificial neural network (MLP-ANN) models. These classification models were then employed for database analysis and utilised to produce false colour images from complete tissue maps of FT-IR microspectra. An important aspect of this study was also to demonstrate how the diagnostic sensitivity and specificity can be specifically optimised. An example is given which shows that changes of the number of teaching patterns per class can be used to modify these two interrelated test parameters. The definition of ANN topology turned out to be crucial to achieve a high degree of correspondence between the gold standard of histopathology and IR spectroscopy. Particularly, a hierarchical scheme of ANN classification proved to be superior for the reliable classification of tissue spectra. It was found that unsupervised methods of clustering, specifically agglomerative hierarchical clustering (AHC), were helpful in the initial phases of model generation. Optimal classification results could be achieved if the class definitions for the ANNs were carried out by considering the classification information provided by cluster analysis.

Diagnosing benign and malignant lesions in breast tissue sections by using IR-microspectroscopy.

The collection of IR spectra through microscope optics and the visualization of the IR data by IR imaging represent a visualization approach, which uses infrared spectral features as a native intrinsic contrast mechanism. To illustrate the potential of this spectroscopic methodology in breast cancer research, we have acquired IR-microspectroscopic data from benign and malignant lesions in breast tissue sections by point microscopy with spot sizes of 30-40 microm. Four classes of distinct breast tissue spectra were defined and stored in the data base: fibroadenoma (a total of 1175 spectra from 14 patients), ductal carcinoma in situ (a total of 1349 spectra from 8 patients), connective tissue (a total of 464 spectra), and adipose tissue (a total of 146 spectra). Artifical neural network analysis, a supervised pattern recognition method, was used to develop an automated classifier to separate the four classes. After training the artifical neural network classifier, infrared spectra of independent external validation data sets ("unknown spectra") were analyzed. In this way, all spectra (a total of 386) taken from micro areas inside the epithelium of fibroadenomas from 4 patients were correctly classified. Out of the 421 spectra taken from micro areas of the in situ component of invasive ductal carcinomas of 3 patients, 93% were correctly identified. Based on these results, the potential of the IR-microspectroscopic approach for diagnosing breast tissue lesions is discussed.

Imaging of colorectal adenocarcinoma using FT-IR microspectroscopy and cluster analysis.

In this paper, three different clustering algorithms were applied to assemble infrared (IR) spectral maps from IR microspectra of tissues. Using spectra from a colorectal adenocarcinoma section, we show how IR images can be assembled by agglomerative hierarchical (AH) clustering (Ward's technique), fuzzy C-means (FCM) clustering, and k-means (KM) clustering. We discuss practical problems of IR imaging on tissues such as the influence of spectral quality and data pretreatment on image quality. Furthermore, the applicability of cluster algorithms to the spatially resolved microspectroscopic data and the degree of correlation between distinct cluster images and histopathology are compared. The use of any of the clustering algorithms dramatically increased the information content of the IR images, as compared to univariate methods of IR imaging (functional group mapping). Among the cluster imaging methods, AH clustering (Ward's algorithm) proved to be the best method in terms of tissue structure differentiation.

Diversity of grass-associated Microbacteriaceae isolated from the phyllosphere and litter layer after mulching the sward; polyphasic characterization of Subtercola pratensis sp. nov., Curtobacterium herbarum sp. nov. and Plantibacter flavus gen. nov., sp. nov.

A representative selection of coryneform bacteria, isolated from the phyllosphere of grasses and the litter layer after mulching the sward, was characterized by a polyphasic approach to clarify their taxonomic position in the family Microbacteriaceae, with particular reference to potentially plant-pathogenic bacteria. On the basis of 16S rDNA analysis, the isolates can be classified into six genotypes representing the genera Curtobacterium, Clavibacter, Subtercola and a subgroup, which was not affiliated to a known genus. One genotype, belonging to the genus Curtobacterium, had an identical 16S rDNA sequence to reference strains of the Curtobacterium flaccumfaciens pathovars. Another genotype, closely related to the potentially pathogenic Curtobacterium flaccumfaciens, could be distinguished from known species of the genus on the basis of phylogenetic and phenotypic characterization and is consequently proposed as a novel species, Curtobacterium herbarum sp. nov. (type strain P 420/07T DSM 14013T = LMG 19917T). Two genotypes assigned to Clavibacter showed a close relationship to Clavibacter michiganensis subsp. tessellarius, a pathogenic bacterium causing foliar lesions on wheat. A further genotype, which clustered clearly in the genus Subtercola by comparison of 16S rDNA sequences, showed a hitherto undescribed B-type of peptidoglycan containing the diagnostic diamino acids ornithine and 2,4-diaminobutyric acid, in the cell wall; this genotype is proposed as Subtercola pratensis sp. nov. (type strain P 229/10T = DSM 14246T = LMG 21000T). For one genotype, which formed a phylogenetically separate branch in the family of Microbacteriaceae showing chemotaxonomic similarities to the genus Rathayibacter, a novel genus, Plantibacter gen. nov., is proposed; the type species is Plantibacter flavus sp. nov. (type strain P 297/02T = DSM 14012T = LMG 19919T).