Introduction
Since the development of the baculovirus expression vector system (BEVS)
(Smith et al., 1983), insect cells (IC) have been established as a
powerful platform for recombinant protein production. The IC-BEVS is
scalable, capable of producing proteins with complex post-translational
modifications (Ailor and Betenbaugh, 1999; Fernandes et al., 2022a), and
induces high expression of transgenes leading to reduced production
times (Correia et al., 2020; Correia et al., 2022; Fernandes et al.,
2022b). These advantages position IC-BEVS as a potential alternative to
traditional systems in the production of complex products like
virus-like particles (VLPs) and viral vectors such as recombinant
adeno-associated virus (AAV). Nevertheless, the lack of a comprehensive
understanding of the severe impact of the viral infection on the host
cell machinery still poses major challenges to further improve this
expression system.
Efforts have been made to characterize the insect cell host response to
virus infection and/or heterologous gene expression. Technologies such
as metabolomics (Carinhas et al., 2010; Monteiro et al., 2012; Monteiro
et al., 2016), transcriptomics (Chen et al., 2014; Koczka et al., 2018;
Silvano et al., 2022; Wei et al., 2017 and Virgolini et al., 2022) and
proteomics (Carinhas et al., 2011; Nayyar et al., 2017; Yu et al., 2016)
have been employed by our group and others to shed light on the
underlying biological mechanisms of cultured insect cells and BEVS.
Exploring the response to virus infection on a gene expression level
might be especially interesting, as the baculovirus has shown to
take-over the cells gene expression machinery, activating stress
response mechanisms such as apoptosis, and impacting protein folding and
translation mechanisms, among others (Koczka et al., 2018; Wei et al.,
2017; Virgolini et al., 2022).
Recent studies have provided genome and transcriptome references forSpodoptera frugiperda and Trichoplusia ni , (Chen et al.,
2019; Xiao et al., 2020) and such advancements could thereby be a
milestone in the study of gene expression alterations in Sf9 and High
Five insect cells during baculovirus infection and/or heterologous
protein expression. Indeed, an emerging number of transcriptomic studies
in both cell lines can be observed (Koczka et al., 2018; Silvano et al.,
2022; Virgolini et al., 2022), highlighting the interest in
understanding host cell response to guide rational design of targeted
cell line development and process engineering approaches. Nevertheless,
these studies are limited by their approach of assessing cell
populations instead of single cells, thus ignoring potential
heterogeneity within the production platform. Moreover, single-cell RNA
sequencing (scRNA-seq) would have the added benefit of identifying
sub-populations of cells with distinct gene expression profiles, which
might result in phenotypically beneficial traits (Ke et al., 2022).
Single-cell transcriptomics technologies have matured rapidly, allowing
the study of gene expression patterns of tens of thousands of single
cells in an accurate and cost-effective manner. ScRNA-seq has become
standard in evaluating the transcriptome profiles of different cell
types within tissues. Nevertheless, first applications in clonally
derived cell lines as well as virus infection processes have been shown,
each indicating significant heterogeneity within the respective cell
population (Russell et al., 2018; Sun et al., 2020; Tzani et al., 2021).
While this could indicate the potential complexity and/or heterogeneity
in production processes using insect cells and BEVS, the use of
single-cell transcriptome analysis to characterize this expression
system is so far inexistent.
In this study, we implemented for the first time scRNA-seq in Sf9 insect
cells during the production of AAV using a low multiplicity of infection
(MOI), dual-baculovirus infection process, assessing population
heterogeneity and gene expression profiles prior to and along infection.