Rapid characterisation of deep-sea actinomycetes for biotechnology screening programmes

A continual need in natural product discovery is dereplication, that is the ability to exclude previously tested microorganisms from screening programmes. Whole-cell fingerprinting techniques offer an ideal solution to this problem because of their rapidity and reproducibility, dependence on small samples, and automation. One such technique, Curie-point pyrolysis mass spectrometry (PyMS), has been deployed for the characterisation of a unique collection of actinomycetes recovered from Pacific Ocean sediments approximately 2000 to 6500 m below sea level. This paper addresses the question: to what extent are pyrogroups, defined on the basis of PyMS fingerprinting, related to classifications derived from more conventional microbial systematics? A collection of 44 randomly chosen deep-sea rhodococci were coded and subjected to a double-blind PyMS and numerical taxonomic (NT) analysis; the latter sorted the strains into clusters (taxospecies) using large sets of equally weighted phenotypic data. At the end of the experiment the codes were disclosed and the NT classification shown to generate 6 homogeneous clusters corresponding to different deep-sea sites. The matching of these clusters with the resulting pyrogroups was very high with an overall congruence of nearly 98%. Thus, PyMS characterisation is directly ascribable to the phenotypic variation being sought for biotechnology screens. Moreover, the exquisite discriminatory power of PyMS readily revealed infraspecific diversity in these industrially important bacteria.     

Taxonomy and biotransformation activities of some deep-sea actinomycetes

Deep-sea soft sediments from trench systems and depths in the northwestern Pacific Ocean ranging from less than 300 to 10 897 m in depth have been analyzed for three target genera of actinomycetes: Micromonospora, Rhodococcus, and Streptomyces. Only culturable strains, recovered at atmospheric pressure on selective isolation media, have been examined to date. Maximum recoveries of culturable bacteria were greater that 10⁷/ml wet g sediment, but actinomycetes comprised a small proportion of this population (usually less than 1%). The target actinomycetes were isolated at all depths except from the Mariana Trench sediments. Actinomycete colonies were defined initially on the basis of colony morphologies, and preliminary identification then was made by chemotaxonomic tests. Pyrolysis mass spectrometry (PyMS) of deep-sea mycolic acid-containing actinomycetes gave excellent correspondence with numerical (phenetic) taxonomic analyses and subsequently was adopted as a rapid procedure for assessing taxonomic diversity. PyMS analysis enabled several clusters of deep-sea rhodococci to be distinguished that are quite distinct from all type strains. 16S rRNA gene sequence analysis has revealed that several of these marine rhodococci have sequences that are very similar to certain terrestrial species of Rhodococcus and to Dietzia. There is evidence for the intrusion of terrestrial runoff into these deep trench systems, and the inconsistency of the phenotypic and molecular taxonomies may reflect recent speciation events in actinomycetes under the high-pressure conditions of the deep sea. The results of DNA-DNA pairing experiments point to the novelty of Rhodococcus strains recovered from hadal depths in the Izu Bonin Trench. Biotransformation studies of deep-sea bacteria have focused on nitrile compounds. Nitrile-metabolizing bacteria, closely related to rhodococci, have been isolated that grow well at low temperature, high salt concentrations, and high pressures, suggesting that they are of marine origin or have adapted to the deep-sea environment. Received: January 22, 1998 / Accepted: February 16, 1998     

Dereplication for biotechnology screening: PyMS analysis and PCR–RFLP–SSCP (PRS) profiling of 16S rRNA genes of marine and terrestrial actinomycetes

The search for exploitable biology is a major task for biotechnology-based industries. In this context, discrimination between previously tested or recovered micro-organisms (dereplication) is imperative, in order to reduce screening costs by sorting large collections of isolates, which are then subjected to further detailed evaluation. Pyrolysis mass spectrometry (PyMS) is a whole-cell fingerprinting technique that enables the rapid and reproducible sorting of micro-organisms, uses small samples and has the advantage of being fully automated. In this study, we compare chemometric fingerprinting with a ribotyping fingerprinting method, in order to investigate the extent to which pyrogroups formed by PyMS analysis relate to genetic diversity, using polymerase chain reaction-restriction fragment length polymorphism-single-strand conformational polymorphism (PRS). A mixture of environmental strains of mycolic acid containing actinomycetes was used to mimic the selection of colonies from primary isolation plates. The congruence found between the clusters defined by the chemometric and molecular fingerprinting techniques was very high and demonstrated the effectiveness of PyMS as a rapid sorting and dereplicating procedure for putatively novel strains, criteria that are critical for biotechnological screens. Moreover, PyMS analysis revealed significant variation within pyrogroups that contained strains with the same genotypic (PRS) characteristics, thus emphasising its discriminatory capacity at the infraspecies level.     

Rapid quantitative analysis of binary mixtures of Escherichia coli strains using pyrolysis mass spectrometry with multivariate calibration and artificial neural networks

Pyrolysis mass spectrometry (PyMS) and multivariate calibration were used to show the high degree of relatedness between Escherichia coli HB101 and E. coli UB5201. Next, binary mixtures of these two phenotypically closely related E. coli strains were prepared and subjected to PyMS. Fully interconnected feedforward artificial neural networks (ANNs) were used to analyse the pyrolysis mass spectra to obtain quantitative information representative of the level of E. coli UB5201 in E. coli HB101. The ANNs exploited were trained using the standard back propagation algorithm, and the nodes used sigmoidal squashing functions. Accurate quantitative information was obtained for mixtures with >3% E. coli UB5201 in E. coli HB101. To remove noise from the pyrolysis mass spectra and so lower the limit of detection, the spectra were reduced using principal components analysis (PCA) and the first 13 principal components used to train ANNs. These PCA-ANNs allowed accurate estimates at levels as low as 1% E. coli UB5201 in E. coli HB101 to be predicted. In terms of bacterial numbers, it was shown that the limit of detection for PyMS in conjunction with ANNs was 3 × 10⁴ E. coli UB5201 cells in 1·6 × 10⁷ E. coli HB101 cells. It may be concluded that PyMS with ANNs provides a powerful and rapid method for the quantification of mixtures of closely related bacterial strains.     

Characterization of Carnobacterium species by pyrolysis mass spectrometry

L.N. MANCHESTER, A. TOOLE AND R. GOODACRE. 1995. Forty-eight strains of Carnobacterium were examined by pyrolysis mass spectrometry (PyMS). The effects of culture age and reproducibility over a 4 week period were also examined. The results were analysed by multivariate statistical techniques and compared with those from a previous numerical taxonomic study based on morphological, physiological and biochemical characteristics and with studies which used DNA-DNA and 16S rRNA sequence homologies. Taxonomic correlations were observed between the PyMS data and the previous studies. Culture age was observed to have little effect on the mass spectra obtained and the reproducibility study indicated that there was very little variation over the 4 week period. It was concluded that PyMS provides a reliable method for studying carnobacterial classification and provides a rapid way for clarifying and refining subgeneric relationships within the genus Carnobacterium. Further work may also show that it offers a potentially very rapid and accurate method for the identification of Carnobacterium.     

Identification and Discrimination of Oral Asaccharolytic Eubacterium spp. by Pyrolysis Mass Spectrometry and Artificial Neural Networks

Curie-point pyrolysis mass spectra were obtained from 29 oral asaccharolytic Eubacterium strains and 6 abscess isolates previously identified as Peptostreptococcus heliotrinreducens. Pyrolysis mass spectrometry (PyMS) with cluster analysis was able to clarify the taxonomic position of this group of organisms. Artificial neural networks (ANNs) were then trained by supervised learning (with the back-propagation algorithm) to recognize the strains from their pyrolysis mass spectra; all Eubacterium strains were correctly identified, and the abscess isolates were identified as un-named Eubacterium taxon C₂ and were distinct from the type strain of P. heliotrinreducens. These results demonstrate that the combination of PyMS and ANNs provides a rapid and accurate identification technique.     

Discrimination and taxonomy of geographically diverse strains of nitrile-metabolizing actinomycetes using chemometric and molecular sequencing techniques

Mycolic acid-containing actinomycetes capable of metabolizing nitriles were recovered from deep-sea sediments and terrestrial soils by enrichment culture on acetonitrile, benzonitrile, succinonitrile or bromoxynil. A total of 43 nitrile-degrading strains were isolated and, together with previously recovered nitrile-degrading rhodococci, were identified by a polyphasic taxonomic approach, which included mycolic acid profiles, pyrolysis mass spectrometry (PyMS), genomic fingerprinting based on sequence variability of the 16S ribosomal RNA gene using polymerase chain reaction-restriction fragment length polymorphism-single-strand conformational polymorphism, and 16S rRNA gene sequence comparison. Isolates phylogenetically related to Rhodococcus erythropolis dominated the culturable microorganisms from most marine and terrestrial samples. These isolates clustered together in a major pyrogroup that showed high congruence with PRS profiles of the 16S rRNA gene. Such high congruence also was obtained for other recovered isolates that were assigned to species of Rhodococcus and Gordonia. Sequencing data validated the results obtained by PRS analysis and enabled phylogenetic relationships to be established. Some of the recovered bacteria probably represent novel microbial species. The fact that nitrile-metabolizing microorganisms were recovered from a wide range of habitat types suggests that nitrile transforming enzymatic activity is geographically widely distributed in nature.     

Rapid authentication of animal cell lines using pyrolysis mass spectrometry and auto-associative artificial neural networks

Summary Pyrolysis mass spectrometry (PyMS) was used to produce biochemical fingerprints from replicate frozen cell cultures of mouse macrophage hybridoma 2C11-12, human leukaemia K562, baby hamster kidney BHK 21/C13, and mouse tumour BW-O, and a fresh culture of Chinese hamster ovary CHO cells. The dimensionality of these data was reduced by the unsupervised feature extraction pattern recognition technique of auto-associative neural networks. The clusters observed were compared with the groups obtained from the more conventional statistical approaches of hierarchical cluster analysis. It was observed that frozen and fresh cell line cultures gave very different pyrolysis mass spectra. When only the frozen animal cells were analysed by PyMS, auto-associative artificial neural networks (ANNs) were employed to discriminate between them successfully. Furthermore, very similar classifications were observed when the same spectral data were analysed using hierarchical cluster analysis. We demonstrate that this approach can detect the contamination of cell lines with low numbers of bacteria and fungi; this approach could plausibly be extended for the rapid detection of mycoplasma infection in animal cell lines. The major advantages that PyMS offers over more conventional methods used to type cell lines and to screen for microbial infection, such as DNA fingerprinting, are its speed, sensitivity and the ability to analyse hundreds of samples per day. We conclude that the combination of PyMS and ANNs can provide a rapid and accurate discriminatory technique for the authentication of animal cell line cultures.     

Novel rhodococci and other mycolate actinomycetes from the deep sea

A large number of mycolate actinomycetes have been recovered from deep-sea sediments in the NW Pacific Ocean using selective isolation methods. The isolates were putatively assigned to the genus Rhodococcus on the basis of colony characteristics and mycolic acid profiles. The diversity among these isolates and their relationship to type strains of Rhodococcus and other mycolate taxa were assessed by Curie point pyrolysis mass spectrometry (PyMS). Three major (A, C, D) and two minor (B, E) groups were defined by PyMS. Cluster A was a large group of isolates recovered from sediment in the Izu Bonin Trench (2679 m); Cluster C comprised isolates from both the Izu Bonin Trench (6390 and 6499 m) and from the Japan Trench (4418, 6048 and 6455 m). These Cluster C isolates showed close similarity to Dietzia maris and this was subsequently confirmed using molecular methods. Cluster D contained isolates recovered from a sediment taken from a depth of 1168m in Sagami Bay and were identified as members of the terrestrial species Rhodococcus luteus. Clusters B and E had close affinities with members of the genera Gordonia and Mycobacterium. The presence of Thermoactinomyces in certain of the deep-sea sediments studied was indicative of the movement of terrestrial material into the ocean depths.16S ribosomal RNA gene sequence analyses produced excellent definition of most genera of the mycolata, and indicated that the among the deep sea isolates (1) were novel species of Corynebacterium, Gordonia and Mycobacterium, and (2) a Sea of Japan isolate the phylogenetic depth of which suggests the possibility of a new genus. Polyphasic taxonomic analysis revealed considerable diversity among the deep sea rhodococci and evidence for recently diverged species or DNA groups.     

Rapid analysis of the expression of heterologous proteins in Escherichia coli using pyrolysis mass spectrometry and Fourier transform infrared spectroscopy with chemometrics: application to alpha 2-interferon production.

Cell pastes and supernatant Escherichia coli samples, taken from an industrial bioprocess overproducing recombinant alpha 2 IFN were analysed using pyrolysis mass spectrometry (PyMS) and diffuse reflectance-absorbance Fourier transform infrared spectroscopy (FT-IR). PyMS and FT-IR are physico-chemical methods which measure predominantly the bond strengths of molecules and the vibrations of bonds within functional groups, respectively. They therefore give quantitative information about the total biochemical composition of the bioprocess sample. The interpretation of these hyperspectral data, in terms of the quantity of alpha 2 IFN in the cell pastes and supernatant samples was possible only after the application of the 'supervised learning' methods of artificial neural networks (ANNs) and partial least squares (PLS) regression. Both PyMS and FT-IR are novel, rapid and economical methods for the screening and the quantitative analysis of complex biological bioprocess over producing recombinant proteins. Models established using either spectral data set had a similarly satisfactory predictive ability. This shows that whole-reaction mixture spectral methods, which measure all molecules simultaneously, do contain enough information to allow their quantification when the entire spectra are used as the inputs to methods based on supervised learning. Moreover, this is the first study where FT-IR in the mid-IR range has been used to quantify the expression of a heterologous protein directly from fermentation broths and the first study to compare the abilities of PyMS and FT-IR for the quantitative analyses of an industrial bioprocess.     

Rapid screening for metabolite overproduction in fermentor broths, using pyrolysis mass spectrometry with multivariate calibration and artificial neural networks

Binary mixtures of model systems consisting of the antibiotic ampicillin with either Escherichia coli or Staphylococcus auresu were subjected to pyrolysis mass spectrometry (PyMS). To deconvolute the pyrolysis mass spectra, so as to obtain quantitative information on the concentration of ampicilin in the mixtures, partial least squares regression (PLS), principal components regression (PCR), and fully interconnected feedforward artificial neural networks (ANNs) were studied. In the latter case, the weights were modified using the standard backpropagation algorithm, and the nodes used a sigmoidal squsahing funciton. It was found that each of the methods could be used to provide calibration models which gave excellent predictions for the concentrations of ampicillin in samples on which they had not been trained. Furthermore, ANNs trained to predict the amount of ampicilin in E. coli were able to generalise so as to predict the concentration of ampicillin in a S. aureus background, illustrating the robustness of ANNs to rather substantial variations in the biological background. The PyMS of the complex mixture of ampicilin in bacteria could not be expressed simply in terms of additive combinations of the spectra describing the pure components of the mixtures and their relative concentrations. Intermolecular reactions took place in the pyrolysate, leading to a lack of superposition of the spectral components and to a dependence of the normalized mass spectrum on sample size. Samples from fermentations of a single organism in a complex production medium were also analyzed quantitatively for a drug of commercial interest. The drug could also be quantified in a variety of mutant-producing strains cultivated in the same medium. The combination of PyMS and ANNs constitutes a novel, rapid, and convenient method for exploitation in strain improvement screening programs. (c) 1994 John Wiley & Sons, Inc.     

Discrimination of higher plant calluses based on embryogenic capacity and taxonomic classification by pyrolysis mass spectrometry

Pyrolysis mass spectrometry (PyMS) is a rapid, simple, high-resolution analytical method based on thermal degradation of complex material in a vacuum, and has been widely applied to the discrimination of closely related microbial strains. Minimally prepared samples of embryogenic and non-embryogenic calluses derived from various higher plants (sweet potato, morning glory, Korean ginseng, Siberian ginseng, and balloon flower) were subjected to PyMS for spectral fingerprinting. A dendrogram based on the unweighted pair group method, with arithmetic mean of pyrolysis mass spectra, divided the calluses into Siberian ginseng embryogenic callus and the others, which were subsequently divided into embryogenic and non-embryogenic callus groups, regardless of plant species from which the calluses were derived. In the non-embryogenic callus group, the dendrogram was in agreement with the known taxonomy of the plants. These results indicate that PyMS analysis could be applied for discriminating plant calluses based on embryogenic capacity and taxonomic classification.     

The value of pyrolysis mass spectrometry to investigate nosocomial outbreaks caused by Serratia marcescens

Simultaneous outbreaks of S. marcescens infection going on in the Neonatal Intensive Care Unit and the Surgical Department of the same hospital were investigated by pyrolysis mass spectrometry (PyMS). The PyMS analysis of the strains clearly demonstrated that the two outbreaks were caused by different strains. The 14 S. marcescens isolates from the first outbreak were closely related, with the exception of one environmental isolate, which did not harbour the ESBL plasmid, which was present in all other isolates. However, the phage type of all 14 isolates was the same. Among the 9 S. marcescens isolates from the second outbreak, PyMS clearly distinguished 3 that exhibited gentamicin resistance from the remaining 6 gentamicin-susceptible isolates. Phage typing was unhelpful in this case, as none of the isolates were typable. The PyMS typing of nosocomial outbreak strains can reach the level of discrimination approaching that achieved by molecular genetic analysis.     

Rapid identification of streptomycetes by artificial neural network analysis of pyrolysis mass spectra

Abstract An artificial neural network was trained to distinguish between three putatively novel species of Streptomyces using normalised, scaled pyrolysis mass spectra from three representative strains of each of the taxa, each sampled in triplicate. Once trained, the artificial neural network was challenged with spectral data from the original organisms, the 'training set', from additional members of the putative novel taxa and from over a hundred strains representing six other actinomycete genera. All of the streptomycetes were correctly identified but many of the other actinomycetes were mis-identified. A modified network topology was developed to recognise the mass spectral patterns of the non-streptomycete strains. The resultant neural network correctly identified the streptomycetes, whereas all of the remaining actinomycetes were recognised as unknown organisms. The improved artificial neural network provides a rapid, reliable and cost-effective method of identifying members of the three target streptomycete taxa.     

Whole-organism fingerprinting of the genus Carnobacterium using Fourier transform infrared spectroscopy (FT-IR)

Sixty seven strains of Carnobacterium, atypical Lactobacillus, Enterococcus durans, Lactobacillus maltaromicus and Vagacoccus salmoninarum were examined by Fourier transform infrared (FT-IR) spectroscopy. The effects of culture age and reproducibility over a six month period were also investigated. The results were analysed by multivariate statistics and compared with those from a previous numerical phenetic study, a pyrolysis mass spectrometry (PyMS) study and with investigations which used DNA-DNA and 16S rRNA sequencing homologies. Taxonomic correlations were observed between the FT-IR data and these studies. Culture age was observed to have little effect on the spectra obtained. The reproducibility study indicated that there was correlation between spectra produced on two occasions over the six month period. It was concluded that FTIR is a reliable method for investigating carnobacterial classification, and may have further potential as a rapid method for use in Carnobacterium identification.     

Mycobacterium avium-intracellulare from patients with and without AIDS compared by pyrolysis mass spectrometry

Isolates of Mycobacterium avium-intracellulare complex (MAI) from AIDS and non-AIDS patients were compared by pyrolysis mass spectrometry (PyMS). Those from AIDS patients were more closely related to each other than those from non-AIDS patients which were significantly more disparate.     

Pyrolysis mass spectrometry characterisation and numerical taxonomy ofAeromonas spp.

Reference strains (2) and 29 isolates ofAeromonas spp. from clinical material and environmental specimens were characterised in traditional biochemical tests, and in pyrolysis mass spectrometry, which gives data reflecting whole-cell composition. Numerical taxonomic analyses of the data sets were compared with conventional identification at species level, and pathogenic potential, as inferred from the origin of the isolates. Clustering with conventional test reaction patterns showed, for each of the species represented, a clearly defined core group of typical isolates, surrounded by a halo of aberrant strains. One further cluster comprised strains intermediate betweenA. caviae andA. hydrophila, and one strain was grossly atypical in both analyses. Clustering from pyrolysis data corresponded less well with species identification. Broadly, the biochemical division between core and halo strains was supported in pyrolysis forA. caviae andA. sobria, but the main group ofA. hydrophila in pyrolysis comprised strains clustering in the core and halo groups of this species, and three strains intermediate betweenA. hydrophila andA. caviae in biochemical tests. Two further pyrolysis clusters comprised core and halo strains ofA. hydrophila. However, pyrolysis clustering correlated well with inferred pathogenicity, showing four clusters of probable pathogens, six clusters of probable nonpathogens, and one two member cluster of doubtful status. Most strains that clustered in the species haloes, or in species-intermediate groups in biochemical tests, were non-human isolates, or were isolated in the absence of symptomatic infection. The correlation of inferred pathogenicity with biochemical clustering was poorer than that with pyrolysis clustering.Abbreviations CTRP conventional test reaction pattern - PyMS pyrolysis mass spectrometry     

Rapid detection of `rare' actinomycetes in environmental samples

Natural products continue to be a useful source of new leads for the pharmaceutical industry. Actinomycetes are prolific producers of natural products and one strategy to increase the possibility of discovering novel chemical entities is to screen actinomycetes considered 'rare' in the environment and previously under-represented in natural product screening collections. We describe a method using bacteriophage as a marker to detect these actinomycetes in environmental samples. This method allows samples to be pre-screened for the presence of target actinomycetes before lengthy isolation programmes are undertaken.     

Marine actinomycetes: An ongoing source of novel bioactive metabolites

Actinomycetes are virtually unlimited sources of novel compounds with many therapeutic applications and hold a prominent position due to their diversity and proven ability to produce novel bioactive compounds. There are more than 22,000 known microbial secondary metabolites, 70% of which are produced by actinomycetes, 20% from fungi, 7% from Bacillus spp. and 1–2% by other bacteria. Among the actinomycetes, streptomycetes group are considered economically important because out of the approximately more than 10,000 known antibiotics, 50–55% are produced by this genus. The ecological role of actinomycetes in the marine ecosystem is largely neglected and various assumptions meant there was little incentive to isolate marine strains for search and discovery of new drugs. The search for and discovery of rare and new actinomycetes is of significant interest to drug discovery due to a growing need for the development of new and potent therapeutic agents. Modern molecular technologies are adding strength to the target-directed search for detection and isolation of bioactive actinomycetes, and continued development of improved cultivation methods and molecular technologies for accessing the marine environment promises to provide access to this significant new source of chemical diversity with novel/rare actinomycetes including new species of previously reported actinomycetes.