In 2010, when the National Alliance for Advanced Biofuels and Bioproducts (NAABB) consortium began, little was known about the molecular basis of algal biomass or oil production. Very few algal genome sequences were available and efforts to identify the best-producing wild species through bioprospecting approaches had largely stalled after the U.S. Department of Energy's Aquatic Species Program. This lack of knowledge included how reduced carbon was partitioned into storage products like triglycerides or starch and the role played by metabolite remodeling in the accumulation of energy-dense storage products. Furthermore, genetic transformation and metabolic engineering approaches to improve algal biomass and oil yields were in their infancy. Genome sequencing and transcriptional profiling were becoming less expensive, however; and the tools to annotate gene expression profiles under various growth and engineered conditions were just starting to be developed for algae. It was in this context that an integrated algal biology program was introduced in the NAABB to address the greatest constraints limiting algal biomass yield. This review describes the NAABB algal biology program, including hypotheses, research objectives, and strategies to move algal biology research into the twenty-first century and to realize the greatest potential of algae biomass systems to produce biofuels.
Background: Yersinia pestis is a category A infective agent that causes bubonic, septicemic, and pneumonic plague. Notably, the acquisition of antimicrobial or multidrug resistance through natural or purposed means qualifies Y. pestis as a potential biothreat agent. Therefore, high-quality antibodies designed for accurate and sensitive Y. pestis diagnostics, and therapeutics potentiating or replacing traditional antibiotics are of utmost need for national security and public health preparedness. Methods: Here, we describe a set of human monoclonal immunoglobulins (IgG1s) targeting Y. pestis fraction 1 (F1) antigen, previously derived from in vitro evolution of a phagedisplay library of single-chain antibodies (scFv). We extensively characterized these antibodies and their effect on bacterial and mammalian cells via: ELISA, flow cytometry, mass spectrometry, spectroscopy, and various metabolic assays. Results: Two of our anti-F1 IgG (αF1Ig 2 and αF1Ig 8) stood out for high production yield, specificity, and stability. These two antibodies were additionally attractive in that they displayed picomolar affinity, did not compete when binding Y. pestis, and retained immunoreactivity upon chemical derivatization. Most importantly, these antibodies detected <1,000 Y. pestis cells in sandwich ELISA, did not harm respiratory epithelial cells, induced Y. pestis agglutination at low concentration (350 nM), and caused apparent reduction in cell growth when radiolabeled at a nonagglutinating concentration (34 nM). Conclusion: These antibodies are amenable to the development of accurate and sensitive diagnostics and immuno/radioimmunotherapeutics.
We have developed a high-throughput approach using frontal affinity chromatography coupled to mass spectrometry (FAC-MS) for the identification and characterization of the small molecules that modulate transcriptional regulator (TR) binding to TR targets. We tested this approach using the methionine biosynthesis regulator (MetJ). We used effector mixtures containing S-adenosyl-L-methionine (SAM) and S-adenosyl derivatives as potential ligands for MetJ binding. The differences in the elution time of different compounds allowed us to rank the binding affinity of each compound. Consistent with previous results, FAC-MS showed that SAM binds to MetJ with the highest affinity. In addition, adenine and 5′-deoxy-5′-(methylthio)adenosine bind to the effector binding site on MetJ. Our experiments with MetJ demonstrate that FAC-MS is capable of screening complex mixtures of molecules and identifying high-affinity binders to TRs. In addition, FAC-MS experiments can be used to discriminate between specific and nonspecific binding of the effectors as well as to estimate the dissociation constant (Kd) for effector-TR binding.
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