Bioinformatics-driven discovery of novel Clostridioides difficile lysins and experimental comparison with highly active benchmarks.
Bioinformatics-driven discovery of novel Clostridioides difficile lysins and experimental comparison with highly active benchmarks.
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DOI:
10.1002/bit.27759
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发表时间:
2021-07
影响因子:
3.8
通讯作者:
Griswold, Karl E.
中科院分区:
文献类型:
--
作者:
Furlon, Jacob M.;Mitchell, Spencer J.;Bailey-Kellogg, Chris;Griswold, Karl E.
Clostridioides difficile is the single most deadly bacterial pathogen in the United States, and its global prevalence and outsized health impacts underscore the need for more effective therapeutic options. Towards this goal, a novel group of modified peptidoglycan hydrolases with significant in vitro bactericidal activity have emerged as potential candidates for treating C. difficile infections (CDI). To date, discovery and development efforts directed at these CDI-specific lysins have been limited, and in particular there has been no systematic comparison of known or newly discovered lysin candidates. Here, we detail bioinformatics-driven discovery of six new anti-C. difficile lysins belonging to the amidase-3 family of enzymes, and we describe experimental comparison of their respective catalytic domains (CATs) with highly active CATs from the literature. Our quantitative analyses include metrics for expression level, inherent antibacterial activity, breadth of strain selectivity, killing of germinating spores, and structural and functional measures of thermal stability. Importantly, prior studies have not examined stability as a performance metric, and our results show that the panel of eight enzymes possess widely variable thermal denaturation temperatures and resistance to heat inactivation, including some enzymes that exhibit marginal stability at body temperature. Ultimately, no single enzyme dominated with respect to all performance measures, suggesting the need for a balanced assessment of lysin properties during efforts to find, engineer, and develop candidates with true clinical potential.
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DOI:
10.1056/nejmoa1910215
发表时间:
2020-04-02
期刊:
The New England journal of medicine
影响因子:
--
作者:
Guh AY;Mu Y;Winston LG;Johnston H;Olson D;Farley MM;Wilson LE;Holzbauer SM;Phipps EC;Dumyati GK;Beldavs ZG;Kainer MA;Karlsson M;Gerding DN;McDonald LC;Emerging Infections Program Clostridioides difficile Infection Working Group
通讯作者:
Emerging Infections Program Clostridioides difficile Infection Working Group
影响因子:
3.4
作者:
Lee YY;Erdogan A;Rao SS
通讯作者:
Rao SS
DOI:
10.1093/bioinformatics/btp163
发表时间:
2009-06-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Cock PJ;Antao T;Chang JT;Chapman BA;Cox CJ;Dalke A;Friedberg I;Hamelryck T;Kauff F;Wilczynski B;de Hoon MJ
通讯作者:
de Hoon MJ
DOI:
10.1093/bioinformatics/bts565
发表时间:
2012-12-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Fu L;Niu B;Zhu Z;Wu S;Li W
通讯作者:
Li W
影响因子:
4.4
作者:
Mehta, Krunal K.;Paskaleva, Elena E.;Kane, Ravi S.
通讯作者:
Kane, Ravi S.