ABSTRACT
Analysis of enteric microbiota function indirectly through the fecal metabolome has the potential to be an informative diagnostic tool. However, metabolomic analysis of feces is hampered by high concentrations of macromolecules such as proteins, fats, and fiber in samples. Three methods-ultrafiltration (UF), Bligh-Dyer (BD), and no extraction (samples added directly to buffer, vortexed, and centrifuged)-were tested on multiple rat (n = 10) and chicken (n = 8) fecal samples to ascertain whether the methods worked equally well across species and individuals. An in silico baseline correction method was evaluated to determine if an algorithm could produce spectra similar to those obtained via UF. For both rat and chicken feces, UF removed all macromolecules and produced no baseline distortion among samples. By contrast, the BD and no extraction methods did not remove all the macromolecules and produced baseline distortions. The application of in silico baseline correction produced spectra comparable to UF spectra. In the case of no extraction, more intense peaks were produced. This suggests that baseline correction may be a cost-effective method for metabolomic analyses of fecal samples and an alternative to UF. UF was the most versatile and efficient extraction method; however, BD and no extraction followed by baseline correction can produce comparable results.
ABSTRACT
The Single Domain Antibody Database, or sdAb-DB, ( www.sdab-db.ca ) is the first freely available repository for single domain antibodies and related classes of proteins. Due to their small size, modular structure, and ease of expression, single domain antibodies (sdAb) have a wide range of applications, including as a rational design tool, and are therefore of great interest for synthetic biologists and bioengineers. However, to enable effective use and sharing of existing sdAbs, including those with engineered functions ( e.g., fusions with fluorescent proteins), as well as the rational design and engineering of new sdAbs, it is necessary to have access to sequences and experimental data. We have therefore developed a publicly available, sdAb-focused database, providing access to manually curated sdAb data from protein databases, published scientific articles, and user submissions. The sdAb-DB is an open-source repository and sharing platform for the sdAb community, providing access to performance data and basic bioinformatic tools for use with previously described and validated sdAbs, as well as for the engineering of new sdAb-based designs and proteins.
