Abstract
Agricultural pests such as slugs are very damaging to plants, leading to the loss of tons of crops every
year. Looking at the long-lasting detrimental effect of chemical pesticide, biological control methods
which involve the use of pests’ natural parasites are gaining popularity. Parasitic nematode of
terrestrial gastropods and entomopathogenic nematodes are groups of parasitic nematodes which
are known to infect a large number of gastropods and insects respectively and are used against many
agricultural and horticultural pests.
The aim of this work is to identify and evaluate the metabolic capabilities of Phasmarhabditis
californica, a lethal parasite of terrestrial gastropods (slugs) to improve its industrial scale production.
As a starting point, Steinernema feltiae, a well-curated, industrially established nematode, was
analysed to identify its metabolic characteristics via a systematic study.
To identify the metabolic capabilities of S. feltiae and P. californica, an integrated approach was
employed by using gene expression data from Infective Juvenile and Young adult as an input to
reconstruct Genome-Scale Metabolic Networks (GEMs) of both developmental stages. For S. feltiae
previously published transcriptomics data was used while for P. californica, a life stage specific
transcriptome was generated and analysed. Accurate descriptions of metabolic states can be achieved
by integrating transcriptomics data into the GEMs.
Flux balance analysis (FBA) was performed to check the connectivity patterns of the metabolic
network and analyse the response to different conditions affecting their metabolism and physiology,
such as varying oxygen, amino acids, and cofactor availability. Simulations revealed that both parasitic
nematodes are auxotrophic for amino acids like histidine, leucine, tryptophan, and phenylalanine. It
was also identified that in oxygen limiting conditions, Infective Juvenile switches its main source of
energy from lipids to carbohydrates, while Young Adults fail to survive in anaerobic conditions. These
results are in good agreement with (and explain) empirical observations in production processes and
could only be achieved due to integration of life-stage specific gene expression profiles with metabolic
models.
The results obtained from transcriptomics data driven metabolic modelling of Young Adult and
Infective Juvenile stages confirm that these approaches reproduce the experimental results to a
certain extent and thus can be employed further for generation of hypotheses and minimization of
the efforts required for devising wet lab experiments in different physiological conditions. The results
could help in formulating optimized growth media and conditions for improved industrial production.