Bacterial Glycoprofiling by Using Random Sequence Peptide Microarrays

Abstract

Current analytical methods have been slow in addressing the growing need for glyco-analysis. A new generation of more empirical high-throughput (HTP) tools is needed to aid the advance of this important field. To this end, we have developed a new HTP screening platform for identification of surface-immobilized peptides that specifically bind O-antigenic glycans of bacterial lipopolysaccharides (LPS). This method involves screening of random sequence peptide libraries in addressable high-density microarray format with the newly developed luminescent LPS-quantum dot micelles. Screening of LPS fractions from O111:B4 and O55:B5 serotypes of E. coli on a microarray consisting of 10,000 20-mer peptide features revealed minor differences, while comparison of LPS from E. coli O111:B4 and P. aeruginosa produced sets of highly specific peptides. Peptides strongly binding to the E. coli LPS were highly enriched in aromatic and cationic amino acids, and most of these inhibited growth of E. coli. Flow cytometry and isothermal titration calorimetry (ITC) experiments showed that some of these peptides bind LPS in-solution with a K(d) of 1.75 microM. Peptide selections against P. aeruginosa were largely composed of hydrogen-bond forming amino acids in accordance with dramatic compositional differences in O-antigenic glycans in E. coli and P. aeruginosa. While the main value of this approach lies in the ability to rapidly differentiate bacterial and possibly other complex glycans, the peptides discovered here can potentially be used off-array as antiendotoxic and antimicrobial lead compounds, and on-array/on-bead as diagnostic and affinity reagents.

Exploring Antibody Recognition of Sequence Space through Random-Sequence Peptide Microarrays

“…Random sequence peptide arrays were produced as described in Morales Betanzos et al (11). Briefly, 10 K random 17-mer sequences containing equal probability of the 20 amino acids except cysteine were generated.…”

A Technology for Developing Synbodies with Antibacterial Activity

“…The composition of each peptide is known, but generated by a random number generator using 19 aa (cysteine was omitted). We found that the (3-aminopropyl)triethoxysilane (APTES) microarray surface chemistry used in earlier published reports of screening proteins, antibodies and carbohydrates [18], [23]–[25] showed high levels of non-specific binding to the interstitial regions of the array and low level binding to peptide spots when whole bacterial cells were screened. To address these issues we developed an alternative microarray surface chemistry using a hyperbranched polymer that reduced non-specific binding and increased the peptide density (Figure S1).…”

Diagnosis and early detection of CNS-SLE in MRL/lpr mice using peptide microarrays

“…This technology has been used in other studies to determine binding patterns specific to that disease, such as Alzheimer’s [16], and we expect that for each disease there will be a different binding pattern that could allow us to distinguish one illness from another ([32,33] and unpublished data). In the future, it would be good to test our microarray technology on other autoimmune diseases to ensure that our tests can distinguish one autoimmune disease from another.…”