INTRODUCTION

Antimicrobial resistance (AMR) has become a major public health threat in the 21st century [1]. Drug-resistant infections were associated with more than 4.95 million deaths globally in 2019 and are projected to cause up to 10 million deaths annually by 2050 if effective mitigation strategies are not implemented [2]. AMR is a multifaceted challenge driven by interactions among humans, animals, and the environment under the One Health framework. Increasing territorial overlap between humans and wildlife has intensified interactions with free-living animals, including those associated with tourism-related wildlife feeding activities [3, 4]. Previous studies have shown that human-associated factors, including captivity, dietary modification, and other anthropogenic influences, can alter the diversity and composition of the gut microbiome in primates [5]. Ecotourism activities such as feeding, petting, and photography further reduce the natural separation between humans and free-living macaques, potentially increasing the risk of pathogen transmission, including antimicrobial-resistant microorganisms [6]. However, the effects of feeding practices, habitat variation, and wildlife ecology on gut microbiota composition and AMR dynamics remain incompletely understood.

The gut microbiota comprises diverse microorganisms inhabiting the gastrointestinal tract and plays essential roles in host physiology through nutrient metabolism, xenobiotic and drug metabolism, immunomo-dulation, and protection against pathogens [7, 8]. Antimicrobial use, together with host- and environment-related factors such as habitat characteristics and dietary composition, can exert selective pressure on gut microbial communities, promoting the persistence and expansion of antimicrobial-resistant bacteria [9]. Furthermore, metagenomic and binning analyses have demonstrated that anthropogenic pressures increase the abundance of dominant AMR gene hosts and facilitate the emergence and dissemination of multidrug- and β-lactam-resistant microorganisms across environmental gradients [10]. E. coli and Salmonella spp. are among the most important zoonotic bacterial pathogens associated with foodborne illnesses worldwide, and resistance in both groups has increased substantially in recent years [11, 12]. Escherichia spp., common gut commensals in humans and macaques, are widely used as model organisms for investigating bacterial pathogenesis and epidemiological transmission. Importantly, commensal E. coli may serve as reservoirs of AMR and virulence genes that can be transmitted between humans and animals through the fecal–oral route [13, 14]. In contrast, Salmonella spp. are major foodborne pathogens commonly transmitted through fecally contaminated food and water [15–17].

Long-tailed macaques (Macaca fascicularis) are non-human primates (NHPs) widely distributed throughout Thailand [18]. These animals are frequently exposed to human activities through tourism, urbanization, and increasing habitat encroachment, resulting in close interactions among macaques, humans, livestock, and domestic animals within shared environments. Such interactions often contribute to human–macaque conflict and may facilitate the exchange of microorganisms and AMR determinants. Previous metagenomic studies have characterized resistome diversity in wild and captive macaques [19], demonstrating greater ARG diversity in semi-captive populations and substantial alterations in the gut microbiota of Thai long-tailed macaques exposed to captivity or anthropogenic feeding [20]. Nevertheless, these studies primarily identify the presence of resistance genes and do not determine whether such genes are actively expressed at the protein level.

Despite increasing interest in wildlife-associated AMR, significant knowledge gaps remain regarding the functional expression of resistance mechanisms within the gut microbiota of free-living NHPs. Most available studies have relied on culture-based methods, metagenomics, or resistome profiling approaches that identify resistance genes but cannot determine their translation into biologically active proteins. Consequently, the actual resistance mechanisms operating within wildlife gut ecosystems remain poorly understood. Moreover, information on how habitat characteristics, anthropogenic pressures, dietary differences, and geographic variation influence the expression of AMR-associated proteins in Escherichia spp. and Salmonella spp. is particularly limited. To date, no study has applied shotgun metaproteomics to characterize active AMR-related protein expression in free-living M. fascicularis inhabiting ecologically distinct environments in Thailand. Addressing this gap is essential for understanding the functional ecology of wildlife resistomes and clarifying the role of free-living macaques as potential reservoirs and disseminators of antimicrobial-resistant microorganisms at the human–wildlife interface.

Therefore, this study aimed to characterize habitat-specific AMR-associated protein expression in Escherichia spp. and Salmonella spp. within the gut resistome of free-living long-tailed macaques inhabiting two ecologically distinct environments in Thailand using a shotgun metaproteomics approach. Specifically, we sought to identify differentially expressed proteins, determine their functional annotations, and evaluate AMR-associated pathways in macaque populations exposed to varying degrees of anthropogenic influence. Metaproteomics provides direct insights into microbial functional activity and enables the identification of actively expressed resistance mechanisms beyond the mere presence of genes [21]. We hypothesized that macaques inhabiting urban-proximate environments would exhibit greater expression and diversity of AMR-associated proteins than macaques in natural ecotourism habitats due to increased exposure to anthropogenic pressures. The findings of this study provide novel insights into the functional ecology of wildlife-associated AMR, improve understanding of habitat-driven variation in gut resistomes, and support the development of evidence-based surveillance and mitigation strategies within a One Health framework.