Limitations in biomass availability restrict the use of chemical analysis methods to highly sensitive approaches. Mass spectrometry was chosen due to its ability to provide information on molecular composition from limited amounts of starting material. To enable robust conductivity, the conductive molecules are highly embedded in surrounding proteins that provide structure and form a protective layer. Purification of the molecules from this layer provided an additional challenge, and prevented isolation without destroying their original structure and orientation. Therefore, mass spectrometry imaging was selected as primary strategy, as it enables chemical characterization from native surfaces.
Since the use of highly specialized mass spectrometric imaging techniques is often restricted to dedicated research infrastructures, a wide-spanning network of collaborations was set up within Belgium, but also included labs in the Netherlands, Germany and the United Kingdom as partners. With these external collaborators, a range of mass-spectrometric imaging techniques was applied to our samples, with varying degrees of sensitivity, mass accuracy, and mass and 3D spatial resolution.
Next to bacterial samples, synthetic NiBiD reference compounds were analyzed as control samples during method development. Method development was performed in 3 stages, including sample preparation, data acquisition, and data analysis. Sample-preparation was optimized to produce surfaces enriched in cofactor material, while reducing background signal. Data acquisition was tuned to increase the information content of mass spectra. For data analysis, untargeted metabolomics pipelines were developed to improve the annotation of Ni/S compounds. Produced pipelines enable multivariate analysis, molecular formula prediction, isotope simulation, and statistical scoring of predicted formulas.
Initial results have confirmed the Ni/S character of the cofactor but have also produced hypothesis shifts regarding its size and stability, which helped us to identify primary bottlenecks for follow-up research Finally, a roadmap was constructed that provides the essential steps towards full identification of the cofactor composition.
