Integrative Analysis of Nontargeted LC-HRMS and High-Throughput Metabarcoding Data for Aquatic Environmental Studies Using Combined Multivariate Statistical Approaches

Significant progress in high-throughput analytical techniques
has
paved the way for novel approaches to integrating data sets from different
compartments. This study leverages nontarget screening (NTS) via liquid
chromatography-high-resolution mass spectrometry (LC-HRMS), a crucial
technique for analyzing organic micropollutants and their transformation
products, in combination with biological indicators. We propose a
combined multivariate data processing framework that integrates LC-HRMS-based
NTS data with other high-throughput data sets, exemplified here by
18S V9 rRNA and full-length 16S rRNA gene metabarcoding data sets.
The power of data fusion is demonstrated by systematically evaluating
the impact of treated wastewater (TWW) over time on an aquatic ecosystem
through a controlled mesocosm experiment. Highly compressed NTS data
were compiled through the implementation of the region of interest-multivariate
curve resolution-alternating least-squares (MCR-ALS) method, known
as ROIMCR. By integrating ANOVA-simultaneous component analysis with
structural learning and integrative decomposition (SLIDE), the innovative
SLIDE-ASCA approach enables the decomposition of global and partial
common, as well as distinct variation sources arising from experimental
factors and their possible interactions. SLIDE-ASCA results indicate
that temporal variability explains a much larger portion of the variance
(74.6%) than the treatment effect, with both contributing to global
shared space variation (41%). Design structure benefits include enhanced
interpretability, improved detection of key features, and a more accurate
representation of complex interactions between chemical and biological
data. This approach offers a greater understanding of the natural
and wastewater-influenced temporal patterns for each data source,
as well as reveals associations between chemical and biological markers
in an exemplified perturbed aquatic ecosystem.