Back

Genomic and Kinetic Modeling Involving Nanoparticle-Mediated Delivery of a Novel Chitinase Enzyme to Outpace Tuta absoluta Damage

Ispirli, Y.; Can, A.; Kececi, M.; Sahin, S. S.; Ayan, S. E.; Baysal, O.

2026-06-23 biochemistry
10.64898/2026.06.23.733920 bioRxiv
Show abstract

The tomato leafminer, Tuta absoluta, poses a severe global agricultural threat due to its rapid leaf-mining behavior and swift development of resistance to conventional chemical pesticides. While microbial chitinases are potent biopesticides, their field efficacy is limited by environmental degradation and the short exposure window before larvae penetrate leaf tissues. This study evaluates a stimuli-responsive, controlled-release nanobiopesticide system utilizing a novel chitinase from newly characterized Serratia marcescens GBS19. A 61.1 kDa chitinase (GBS19_ChiA) was heterologously expressed in Escherichia coli and purified to a specific activity of 215.01 U/mg. The enzyme was immobilized onto starch-coated silica nanoparticles designed for target-triggered release via host alpha-amylase. Genomic profiling and R-based kinetic modeling were integrated to evaluate the efficacy of purified and immobilized forms against T. absoluta. Immobilization enhanced thermal and pH stability, with the nanocarrier maintaining 85% activity over 10 weeks. In larval bioassays, immobilization increased mortality from 21.9% to 59.4% (5000 U/mL) by day 3, reaching 62.5% by day 6. Genomic analysis identified an expansive secretome and a Type VI Secretion System (T6SS), characterizing GBS19 as a multi-pronged pathogen. Kinetic modeling established that while immobilized enzymes are effective, the 2.5-hour exposure time on T. absoluta requires the synergistic action of chitinases (ChiA/B/C) to reach the lethal desiccation threshold before larvae establish protective mines. Starch-coated silica nanoparticles significantly improve chitinase stability and delivery. However, overcoming the rapid penetration of T. absoluta necessitates a whole-cell or multi-enzyme synergistic approach to outpace larval behavioural defences.

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

1
PLOS ONE
5266 papers in training set
Top 21%
8.0%
2
Pest Management Science
36 papers in training set
Top 0.1%
5.6%
3
Applied and Environmental Microbiology
339 papers in training set
Top 1%
5.6%
4
Scientific Reports
3612 papers in training set
Top 15%
5.6%
5
Nature Communications
5641 papers in training set
Top 26%
5.6%
6
ACS Synthetic Biology
287 papers in training set
Top 0.7%
4.9%
7
Water Research
79 papers in training set
Top 0.4%
4.1%
8
Journal of Hazardous Materials
21 papers in training set
Top 0.1%
3.3%
9
International Journal of Biological Macromolecules
76 papers in training set
Top 0.5%
2.8%
10
Environmental Science & Technology
64 papers in training set
Top 0.5%
2.4%
11
Microbiology Spectrum
469 papers in training set
Top 5%
2.4%
50% of probability mass above
12
PLOS Neglected Tropical Diseases
466 papers in training set
Top 3%
2.2%
13
Advanced Science
286 papers in training set
Top 4%
1.9%
14
Microbial Biotechnology
34 papers in training set
Top 0.4%
1.8%
15
Applied Microbiology and Biotechnology
32 papers in training set
Top 0.4%
1.8%
16
ACS Applied Materials & Interfaces
39 papers in training set
Top 0.6%
1.5%
17
ACS Applied Bio Materials
24 papers in training set
Top 0.5%
1.4%
18
Communications Chemistry
48 papers in training set
Top 0.8%
1.4%
19
Science Advances
1243 papers in training set
Top 24%
1.1%
20
Frontiers in Plant Science
256 papers in training set
Top 3%
1.1%
21
mBio
833 papers in training set
Top 10%
1.0%
22
mSystems
394 papers in training set
Top 6%
1.0%
23
SLAS Technology
14 papers in training set
Top 0.2%
0.9%
24
Analytical Chemistry
218 papers in training set
Top 2%
0.9%
25
Plants
43 papers in training set
Top 1%
0.9%
26
Peer Community Journal
281 papers in training set
Top 5%
0.9%
27
Environmental Pollution
37 papers in training set
Top 1%
0.9%
28
Environmental Microbiome
29 papers in training set
Top 0.7%
0.9%
29
Journal of Hospital Infection
29 papers in training set
Top 0.4%
0.9%
30
FEMS Microbiology Ecology
54 papers in training set
Top 1%
0.9%