**1. Introduction**

Highly effective antibiotics have been waning since they were introduced into the clinic to treat infectious diseases more than 75 years ago. Antibacterial-resistant bacteria account for approximately 700,000 deaths each year worldwide [1]. The near-empty pharmaceutical pipeline for new antibiotics has now reached alarming levels. In 2017, the World Health Organization (WHO) released a list of antibiotic-resistant "priority pathogens" that posed the greatest threat to human health for the first time, reminding that we were stepping into the post-antibiotic era [2]. Therefore, the urgen<sup>t</sup> need for new antimicrobial agents has augmented scientists' interest in discovering new antibiotics.

Natural products have a profound role in drug discovery and development [3]. Between 1981 and 2019, natural products and their derivatives accounted for 55% of the 162 new antibacterial chemical entities [4]. The strains in the class *Actinomycetia* (former class *Actinobacteria*) [5], especially species of the genus *Streptomyces*, are known as a rich source of novel antibiotics [6–9]. However, finding novel antibiotics from in-depth investigated terrestrial microorganisms has become more challenging. Researchers have been exploring untapped sources of biodiversity for novel pharmaceutical compounds, such as the deep sea [10], deserts [11], polar areas [12], and mangroves [13,14]. Because of its high moisture, high salinity, and hypoxia-tolerant ecosystem in the intertidal zones, the mangrove ecosystem is unique and contains a wealth of undiscovered bacteria and natural products, making it a focus area for bioactive natural product discovery [15]. To the best of our knowledge, very little research has been carried out on bioprospecting of Leizhou Peninsula mangrove actinomycetia. Only a few reports describing actinomycetia isolated from this ecosystem have been published so far, and no research on prioritizing the actinomycetial strains and discovering their secondary metabolites has been carried out [16–18].

The selection of strain candidates from large strain collections using traditional bioactivity screening and/or taxonomy-based methods usually result in the reisolation of known compounds [19,20]. Nowadays, exploring new bioactive compounds from microbial strains has moved toward integrated strategies, which combine phylogenetic data and bioactivity tests with dereplication approaches for rapid identification of known bioactive metabolites. Dereplication using chromatographic and spectroscopic methods and database searches can save time and avoid repetitive work during natural product discovery programs. Recently, a new dereplication method was developed by Tim Bugni using chemical dereplication coupled with metabolomics tools [21]. By incorporating metabolomics approaches, dereplication can focus on chemically diverse bacterial extracts from the bioactive strains, and this new method has shown to be effective in discovering putative new bioactive compounds and is frequently employed in microbial drug discovery programs.

Metabolomics is the comprehensive analysis of small molecule metabolites in a biological system to reflect the phenotype of its genomic, transcriptomic, and proteomic networks, providing insight into the biological functions [22]. In the past, metabolomics was mainly used to investigate primary metabolites, such as nucleotides, amino acids, and lipids. However, the majority of modern metabolomics coupled with molecular networking is readily applied to secondary metabolites discovery for new natural products. Combined principal component analysis (PCA) with LC/MS-based metabolomics is an efficient analytical tool to differentiate the bacterial strains based on their LC/MS profiles [23,24]. The strains producing similar secondary metabolites are clustered together, whereas those with different metabolites are separated. This new approach could significantly accelerate the bioassay-guided selection for chemically distinct strains that might yield novel bioactive secondary metabolites [25–27]. In addition, orthogonal partial least squares-discriminant

analysis (OPLS-DA) is a supervised multivariate analysis that targets bioactive metabolites between the active and inactive groups to give information about the chemical composition of selected active extracts before isolation [19,20,28,29]. Molecular networking, one of the main analysis tools in the GNPS platform, creates structured networking based on MS/MS similarity to reflect the molecular diversity in the extracts. It has been proven to be successful for effective chemical dereplication and novel metabolite discovery [30–32].

In the present study, we employed integrated strategies in prioritizing the actinomycetial strains from the underexplored mangrove soil in Leizhou Peninsula. Actinomycetial strains were isolated using the culture-dependent method and phylogenetically characterized based on 16S rRNA gene sequencing. The selected actinomycetial strains were further subjected to antibacterial assays followed by metabolomics analysis, such as PCA, OPLS-DA, and molecular networking. The obtained data were integrated to prioritize the strains for follow-up chemical isolation and structural identification work of putative new compounds.
