Metabolomics-assisted synthetic biology

As the world progresses from a fossil-fuel based economy to a more sustainable one, synthetic biology will become increasingly important for the production of high-value fine chemicals as well as low-value commodities in bulk. The integration of metabolomics and fluxomics within synthetic biology projects will be vital at all levels, including the initial design of the pathways to be generated, through to the optimisation of those pathways so that more efficient conversion of low-cost starting materials into highly desirable products can be achieved. This review highlights these areas and details the most important and exciting advances being made in this area.     

A new approach to modeling daily probabilities of conception

Standard conception probabilities models assume that different acts of intercourse make independent contributions to the probability of conception in viable cycles. We propose an alternative, approximate model based on the assumption that the act of intercourse closest to the time of maximum fertility is the one most likely to have caused conception. We describe an adaptive algorithm [the most fertile intercourse day (MFID) algorithm] that estimates the most fertile intercourse day in each cycle. The approach is easily extended to include covariates and random between-couple differences in fecundability that affect the probability of conception in a given cycle. Reanalyses of two data sets reported in the literature are presented. Estimates of the probability of conception during the most fertile period of the cycle and of the effects of covariates are similar to estimates found using standard models.     

Differentiation of Micromonospora isolates from a coastal sediment in Wales on the basis of Fourier transform infrared spectroscopy, 16S rRNA sequence analysis, and the amplified fragment length polymorphism technique

A number of actinomycetes isolates were recovered from coastal sediments in Aberystwyth (Wales, United Kingdom) with standard isolation techniques. Most of them were putatively assigned to the genera Streptomyces and Micromonospora on the basis of their morphological characteristics, and there appeared to be no difference whether the isolation media contained distilled water or seawater. A group of 20 Micromonospora isolates was selected to undergo further polyphasic taxonomic investigation. Three approaches were used to analyze the diversity of these isolates, 16S rDNA sequencing, fluorescent amplified fragment length polymorphism (AFLP), and Fourier transform infrared spectroscopy (FT-IR). The 16S rDNA sequence analysis confirmed that all of these isolates should be classified to the genus Micromonospora, and they were analyzed with a group of other Micromonospora 16S rDNA sequences available from the Ribosomal Database Project. The relationships of the 20 isolates were observed after hierarchical clustering, and almost identical clusters were obtained with these three techniques. This has obvious implications for high-throughput screening for novel actinomycetes because FT-IR spectroscopy, which is a rapid and reliable whole-organism fingerprinting method, can be applied as a very useful dereplication tool to indicate which environmental isolates have been cultured previously.     

The deconvolution of pyrolysis mass spectra using genetic programming: application to the identification of some Eubacterium species

Pyrolysis mass spectrometry was used to produce complex biochemical fingerprints of Eubacterium exiguum, E. infirmum, E. tardum and E. timidum. To examine the relationship between these organisms the spectra were clustered by canonical variates analysis, and four clusters, one for each species, were observed. In an earlier study we trained artificial neural networks to identify these clinical isolates successfully; however, the information used by the neural network was not accessible from this so-called `black box' technique. To allow the deconvolution of such complex spectra (in terms of which masses were important for discrimination) it was necessary to develop a system that itself produces `rules' that are readily comprehensible. We here exploit the evolutionary computational technique of genetic programming; this rapidly and automatically produced simple mathematical functions that were also able to classify organisms to each of the four bacterial groups correctly and unambiguously. Since the rules used only a very limited set of masses, from a search space some 50 orders of magnitude greater than the dimensionality actually necessary, visual discrimination of the organisms on the basis of these spectral masses alone was also then possible.     

The use of chemical profiling for monitoring metabolic changes in artificial soil slurries caused by horizontal gene transfer

This study explores the utility of Fourier transform infra-red spectroscopy (FT-IR) as a metabolomic tool to detect changes in water-extractable chemical profile resulting from horizontal gene transfer (HGT) events in artificial soil slurries. A GFP–Km (Green fluorescent protein–kanamycin) cassette tagged HGT recipient Acinetobacter strain ADPWH67 with the salicylate hydroxylase gene (salA) disrupted was introduced to slurries containing either sterile or non-sterile soil. The subsequent addition of naked salA DNA allowed the specific monitoring of HGT events by enumerating GFP-expressing colonies on minimal media with salicylate as a sole carbon source. DNA sequencing confirmed that salA was restored in these transformants. Gene transformation frequencies of around 10⁻⁶ were achieved in the presence of sterile and non-sterile soils. Aqueous extracts of the soil slurries were then analyzed using FT-IR in order to ascertain whether any shifts in chemical profile could be detected. We found that following HGT events FT-IR chemical profiles were clearly altered when analyzed with multivariate statistics. Furthermore, these changes could be explained by differences in key chemical signatures including salicylate as well as other biomolecules found in soils. The slurry extracts were also subjected to GC-MS which confirmed the results of FT-IR analyses. FT-IR was therefore demonstrated to have utility for the rapid screening of metabolomic changes in soils following effective HGT events. In addition, this approach could potentially link specific metabolite changes with corresponding catabolic genes.Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

Glycosylation of recombinant antibody therapeutics

The adaptive immune system has the capacity to produce antibodies with a virtually infinite repertoire of specificities. Recombinant antibodies specific for human targets are established in the clinic as therapeutics and represent a major new class of drug. Therapeutic efficacy depends on the formation of complexes with target molecules and subsequent activation of downstream biologic effector mechanisms that result in elimination of the target. The activation of effector mechanisms is dependent on structural characteristics of the antibody molecule that result from posttranslational modifications, in particular, glycosylation. The production of therapeutic antibody with a consistent human glycoform profile has been and remains a considerable challenge to the biopharmaceutical industry. Recent research has shown that individual glycoforms of antibody may provide optimal efficacy for selected outcomes. Thus a further challenge will be the production of a second generation of antibody therapeutics customized for their clinical indication.     

Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics

¹H nuclear magnetic resonance (¹H NMR)-based metabolomics was utilized to elucidate the earthworm sub-lethal toxicity after exposure to the persistent environmental contaminant phenanthrene. Earthworms were exposed to 0.05, 0.2 and 0.4 mg/cm² of phenanthrene [which correspond to 1/32nd to 1/4th of the 48-h LC₅₀ (concentration that causes 50 % mortality), respectively] via contact tests over 1, 2 and 3 days of dermal contact. ¹H NMR-based metabolomic analysis of the polar and non-polar fractions of the earthworm tissue extracts revealed heightened Eisenia fetida toxic responses with both longer exposure times and higher phenanthrene concentrations. Principal component analysis (PCA) of the polar fraction showed significant separation between control and exposed earthworms along PC1 for all phenanthrene concentrations on each day. The PCA of the non-polar fraction showed significant separation between the controls and exposed earthworms for only the first day of exposure. These results suggested that alanine, glutamate, maltose, and fatty acids were potential indicators of phenanthrene exposure. Interruption in energy production due to a deactivation of the succinate dehydrogenase enzyme in the Krebs cycle was also postulated in exposed earthworms. Cross-validated partial least squares-regression models showed that the polar metabolic profile of E. fetida was weakly but significantly correlated to phenanthrene exposure concentrations after day 1 and day 2 of exposure. Overall, this study indicates that with longer exposures, contact time becomes more important than concentration in discriminating between control and exposed earthworms. This study also shows that NMR-based metabolomics has promise as a powerful ecotoxicological tool for elucidating the mode of toxicity of contaminants.