Gram-positive bacteria are some of the earliest known life forms, diverging from gram-negative bacteria 2 billion years ago. These organisms utilize sortase enzymes to attach proteins to their peptidoglycan cell wall, a structural feature that distinguishes the two types of bacteria. The transpeptidase activity of sortases make them an important tool in protein engineering applications, e.g., in sortase-mediated ligations or sortagging. However, due to relatively low catalytic efficiency, there are ongoing efforts to create better sortase variants for these uses. Here, we use bioinformatics tools, principal component analysis and ancestral sequence reconstruction, in combination with protein biochemistry, to analyze natural sequence variation in these enzymes. Principal component analysis on the sortase superfamily distinguishes previously described classes and identifies regions of relatively high sequence variation in structurally-conserved loops within each sortase family, including those near the active site. Using ancestral sequence reconstruction, we determined sequences of ancestral Staphylococcus and Streptococcus Class A sortase proteins. Enzyme assays revealed that the ancestral Streptococcus enzyme is relatively active and shares similar sequence variation with other Class A Streptococcus sortases. Taken together, we highlight how natural sequence variation can be utilized to investigate this important protein family, arguing that these and similar techniques may be used to discover or design sortases with increased catalytic efficiency and/or selectivity for sortase-mediated ligation experiments.
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Inter- and Intra- Patient ECG Heartbeat Classification for Arrhythmia Detection: A Sequence to Sequence Deep Learning Approach
- Award ID(s):
- 1657260
- NSF-PAR ID:
- 10086899
- Date Published:
- Journal Name:
- ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
- Page Range / eLocation ID:
- 1308 to 1312
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Filament formation by metabolic, biosynthetic, and other enzymes has recently come into focus as a mechanism to fine-tune enzyme activity in the cell. Filamentation is key to the function of SgrAI, a sequence-specific DNA endonuclease that has served as a model system to provide some of the deepest insights into the biophysical characteristics of filamentation and its functional consequences. Structure-function analyses reveal that, in the filamentous state, SgrAI stabilizes an activated enzyme conformation that leads to accelerated DNA cleavage activity and expanded DNA sequence specificity. The latter is thought to be mediated by sequence-specific DNA structure, protein–DNA interactions, and a disorder-to-order transition in the protein, which collectively affect the relative stabilities of the inactive, non-filamentous conformation and the active, filamentous conformation of SgrAI bound to DNA. Full global kinetic modeling of the DNA cleavage pathway reveals a slow, rate-limiting, second-order association rate constant for filament assembly, and simulations of in vivo activity predict that filamentation is superior to non-filamenting mechanisms in ensuring rapid activation and sequestration of SgrAI's DNA cleavage activity on phage DNA and away from the host chromosome. In vivo studies demonstrate the critical requirement for accelerated DNA cleavage by SgrAI in its biological role to safeguard the bacterial host. Collectively, these data have advanced our understanding of how filamentation can regulate enzyme structure and function, while the experimental strategies used for SgrAI can be applied to other enzymatic systems to identify novel functional roles for filamentation.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICASSP.2019.8683140
