Marco Zaccaria
Profile Url: marco-zaccaria
Researcher at Boston College, Department of Biology
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Xylella fastidiosa is an insect vector-transmitted bacterial plant pathogen associated with severe diseases in a wide range of plants. In last decades, X. fastidiosa was detected in several European countries. Among X. fastidiosa subspecies, here we study X. fastidiosa subsp. pauca associated with the Olive Quick Decline Syndrome (OQDS) causing severe losses in Southern Italy. First, we collected Olea europaea L. (cv. Ogliarola salentina) samples in groves located in infected zones and uninfected zones. Secondly, the untargeted LC-TOF analysis of the lipid profiles of OQDS positive (+) and negative (-) plants showed a significant clustering of OQDS+ samples apart from OQDS- ones. Thirdly, using HPLC-MS/MS targeted methods and chemometric analysis, we identified a shortlist of 10 lipids significantly different in the infected versus healthy samples. Last, we observed a clear impact on X. fastidiosa subsp. pauca growth and biofilm formation in vitro liquid cultures supplemented with these compounds. Considering that growth and biofilm formation are primary ways by which X. fastidiosa causes disease, our results demonstrate that lipids produced as part of the plant's immune response can exacerbate the disease. This is reminiscent of an allergic reaction in animal systems, offering the depression of plant immune response as a potential strategy for OQDS treatment
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We demonstrate a path towards full Quantum Mechanics (QM) characterization of enzymatic activity. As a case-study, we investigate the detoxification of aflatoxin, a carcinogenic food contaminant, by laccase, a versatile oxidase capable of--but not efficient for--degrading aflatoxin. We use a combination of quantitative experimentation and QM modeling to show that low enzymatic steric affinity for aflatoxin is the main bottleneck, rather that the oxidative activity of laccase. To identify the structural elements responsible for low reaction rates, we perform a density functional theory (DFT) based modeling of both the substrate and the enzyme in a full QM simulation of more than 7,000 atoms. Thanks to our approach we point to amino acid residues that determine the affinity of laccase for aflatoxin. We show that these residues are substrate-dependent, making a full QM approach necessary for enzyme optimization. Altogether, we establish a roadmap for rational enzyme engineering applicable beyond our case study.
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This work focuses on: 1) the development of a methodology to perform a full Quantum Mechanics (QM) characterization of enzymatic activity; 2) the development of a rational approach to laccase engineering as a food bioremediator. Aflatoxins are among the most dangerous natural carcinogens, and regularly contaminate reserves of staple crops worldwide. Decontamination of aflatoxin-polluted food is of great interest for ensuring food safety, and bioremediation is regarded as the most promising solution. The fungal isoforms of laccase display the rare potential to detoxify aflatoxin by tackling its aromatic moieties.. Yet, because of a generally low efficiency, large-scale application of naturally occurring isoforms has so far been unfeasible. We perform a combination of quantitative experimentation and quantum mechanical modeling on aflatoxin and reveal that: (1) detoxification efficiency is limited by the low enzymatic affinity for the substrate; and (2) aflatoxin is not detoxified by oxidative activity of laccase alone, but requires additional stimulation from the environment. QM modeling also allowed identification of the residues in the laccase tertiary structure that determine affinity of the enzymatic pocket for aflatoxin. We conclude that, for our case-study, a full QM approach is mandatory as a first step towards rational optimization. We detail a feasible approach towards this endeavor and argue that our full QM characterization can serve as a roadmap for enzyme development in other applications pertaining laccase as well as other enzymes.