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<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Nanotechnol.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Nanotechnology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Nanotechnol.</abbrev-journal-title>
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<issn pub-type="epub">2673-3013</issn>
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<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-id pub-id-type="publisher-id">1666431</article-id>
<article-id pub-id-type="doi">10.3389/fnano.2025.1666431</article-id>
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<subj-group subj-group-type="heading">
<subject>Review</subject>
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<title-group>
<article-title>Engineered nanomaterials and the microbiome: assessing disruptions in environmental and human microbial communities</article-title>
<alt-title alt-title-type="left-running-head">Chowdhury and Ghosh</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fnano.2025.1666431">10.3389/fnano.2025.1666431</ext-link>
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<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Chowdhury</surname>
<given-names>Alonkrita</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
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<uri xlink:href="https://loop.frontiersin.org/people/3302058"/>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing&#x2013;review and editing</role>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Ghosh</surname>
<given-names>Mayukh</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
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<xref ref-type="corresp" rid="c001">&#x2a;</xref>
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<aff id="aff1">
<label>1</label>
<institution>Department of Plant Biotechnology, Institute of Agricultural Sciences, Banaras Hindu University</institution>, <city>Varanasi</city>, <country country="IN">India</country>
</aff>
<aff id="aff2">
<label>2</label>
<institution>Department of Veterinary Physiology and Biochemistry, Faculty of Veterinary and Animal Sciences, Institute of Agricultural Sciences, Banaras Hindu University</institution>, <city>Varanasi</city>, <country country="IN">India</country>
</aff>
<author-notes>
<corresp id="c001">
<label>&#x2a;</label>Correspondence: Mayukh Ghosh, <email xlink:href="mailto:ghosh.mayukh87@gmail.com">ghosh.mayukh87@gmail.com</email>
</corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-12-10">
<day>10</day>
<month>12</month>
<year>2025</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>7</volume>
<elocation-id>1666431</elocation-id>
<history>
<date date-type="received">
<day>15</day>
<month>07</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>18</day>
<month>09</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>24</day>
<month>11</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Chowdhury and Ghosh.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Chowdhury and Ghosh</copyright-holder>
<license>
<ali:license_ref start_date="2025-12-10">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<p>The rapid advancement and integration of engineered nanomaterials (ENMs) into consumer products, industrial processes, biomedical applications, and environmental technologies have revolutionized multiple sectors. However, their increased production and environmental release raise critical concerns about unintended interactions with microbial ecosystems. ENMs, including metal-based nanoparticles (silver, titanium dioxide, zinc oxide) and carbon nanomaterials (graphene, carbon nanotubes), possess unique physicochemical properties such as high surface area-to-volume ratios, tunable reactivity, and antimicrobial potential that allow them to interact directly with microbial cells or indirectly influence their habitats. This review critically examines the emerging evidence on ENM&#x2013;microbiome interactions across human, aquatic, terrestrial, and agricultural systems. In human-associated microbiomes, especially the gut, ENMs can induce dysbiosis by disrupting microbial diversity, altering metabolite production (e.g., short-chain fatty acids), and impairing gut barrier integrity, contributing to inflammation and metabolic disorders. In environmental settings, ENMs influence key microbial functions like nitrogen fixation, organic matter decomposition, and biogeochemical cycling, potentially undermining ecosystem stability and agricultural productivity. Moreover, ENMs are increasingly implicated in accelerating antimicrobial resistance by promoting horizontal gene transfer and enriching resistance genes in microbial communities. The review highlights methodological advances such as high-throughput sequencing, meta-omics approaches, <italic>in vitro</italic> colon simulators, and <italic>in vivo</italic> models that have enhanced the assessment of ENM-induced microbiome alterations. Despite these advances, significant gaps remain in understanding long-term and low-dose effects, dose&#x2013;response relationships, and ecological thresholds. Addressing these gaps through multidisciplinary research and regulatory frameworks is essential for ensuring the safe and sustainable deployment of nanotechnologies in a microbiome-sensitive world.</p>
</abstract>
<kwd-group>
<kwd>engineered nanomaterials</kwd>
<kwd>microbiome</kwd>
<kwd>dysbiosis</kwd>
<kwd>antimicrobial resistance</kwd>
<kwd>ecosystem health</kwd>
<kwd>meta-omics technologies</kwd>
</kwd-group>
<funding-group>
<funding-statement>The authors declare that no financial support was received for the research and/or publication of this article.</funding-statement>
</funding-group>
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<fig-count count="4"/>
<table-count count="2"/>
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<ref-count count="300"/>
<page-count count="28"/>
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<custom-meta-group>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Environmental Nanotechnology</meta-value>
</custom-meta>
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</front>
<body>
<sec sec-type="intro" id="s1">
<label>1</label>
<title>Introduction</title>
<p>The emergence and widespread integration of engineered nanomaterials (ENMs) into consumer products, industrial processes, environmental technologies, and biomedical applications has revolutionized multiple sectors of modern life (<xref ref-type="bibr" rid="B24">Bora et al., 2022</xref>; <xref ref-type="bibr" rid="B205">Rocco, 2025</xref>). These nanoscale materials, typically ranging from 1 to 100&#xa0;nm in size, exhibit novel physicochemical properties such as high surface area-to-volume ratio, tunable reactivity, and enhanced mechanical or optical behavior (<xref ref-type="bibr" rid="B124">Kumar A. Y. N. et al., 2024</xref>). Common ENMs include metal-based nanoparticles (NPs), such as silver nanoparticles (AgNPs), titanium dioxide nanoparticles (TiO<sub>2</sub> NPs), zinc oxide nanoparticles (ZnO NPs), carbon-based nanomaterials (CNMs) like graphene, carbon nanotubes (CNTs), and composite nanostructures (<xref ref-type="bibr" rid="B77">Fritea et al., 2021</xref>). While these innovations have brought significant technological and economic benefits, their increasing production and environmental release have raised growing concerns about potential biological and ecological risks, especially concerning their interactions with microbial communities (<xref ref-type="bibr" rid="B195">Rajpal et al., 2025</xref>). Microbial ecosystems spanning human-associated microbiomes to those found in aquatic, terrestrial, and agricultural environments play fundamental roles in maintaining physiological and ecological equilibrium (<xref ref-type="bibr" rid="B148">Ma L. C. et al., 2023</xref>). In the human body, particularly within the gastrointestinal tract, the gut microbiota contributes to digestion, immune regulation, synthesis of essential vitamins and short-chain fatty acids (SCFAs), and defense against pathogens (<xref ref-type="bibr" rid="B216">See et al., 2025</xref>). Similarly, in natural environments, microbial communities regulate biogeochemical cycles, decompose organic matter, support plant growth through symbiosis, and influence soil and water quality. Any disturbance in microbial diversity, abundance, or metabolic function, termed as dysbiosis, can have cascading effects on host health and ecosystem resilience (<xref ref-type="bibr" rid="B191">Prasad et al., 2024</xref>; <xref ref-type="bibr" rid="B285">Zaman et al., 2025</xref>).</p>
<p>ENMs are increasingly recognized as potential disruptors of microbial homeostasis. When released into the environment through waste streams, or ingested or inhaled by humans and animals, ENMs can interact directly with microbial cells or indirectly influence their surrounding microenvironments (<xref ref-type="bibr" rid="B200">Ray et al., 2009</xref>; <xref ref-type="bibr" rid="B126">Kumar et al., 2022</xref>). Their mechanisms of action include generation or induction of reactive oxygen species (ROS), disruption of membrane integrity, interference with DNA and protein function, and modulation of microbial metabolic and signaling pathways (<xref ref-type="bibr" rid="B128">Kumar R. et al., 2024</xref>). These effects can lead to reduced microbial diversity, shifts in community composition, alterations in metabolite production, and perturbation of key functional processes such as nutrient cycling, energy metabolism, and host&#x2013;microbe communication (<xref ref-type="bibr" rid="B256">Wang et al., 2017</xref>). In human systems, such alterations have been linked to inflammatory bowel diseases, metabolic disorders, immune dysregulation, and neurobehavioral conditions (<xref ref-type="bibr" rid="B274">Xuan et al., 2023</xref>). In environmental settings, ENMs can affect microbial-driven processes like nitrogen fixation, denitrification, and organic matter decomposition, ultimately threatening soil fertility, water quality, and ecosystem services (<xref ref-type="bibr" rid="B100">Hochella et al., 2019</xref>; <xref ref-type="bibr" rid="B103">Huang et al., 2024</xref>).</p>
<p>Furthermore, ENMs may play a role in accelerating antimicrobial resistance (AMR) by enhancing horizontal gene transfer, altering microbial stress responses, and promoting the persistence of resistance genes in various environmental matrices (<xref ref-type="bibr" rid="B260">Wang X. et al., 2024</xref>; <xref ref-type="bibr" rid="B187">Piergiacomo et al., 2022</xref>). This poses a dual risk: while ENMs are often employed for their antimicrobial properties, their indiscriminate or chronic use could inadvertently select for resistant strains, complicating both clinical and ecological health management (<xref ref-type="bibr" rid="B4">Alav and Buckner, 2024</xref>).</p>
<p>Given the breadth of these interactions, the current review aims to provide a comprehensive overview of the current understanding of ENM&#x2013;microbiome dynamics, the effects of various NMs on the human gut microbiota, aquatic and soil microbial ecosystems, and the potential for ENMs to influence microbial resistance development. It also evaluates the methodologies used to study these effects, including high-throughput sequencing, omics technologies, and <italic>in vitro</italic>/<italic>in vivo</italic> models, while highlighting regulatory and scientific challenges in assessing long-term risks. Finally, key knowledge gaps are identified and future directions are proposed for ensuring that the deployment of nanotechnologies is conducted safely and sustainably in a microbiome-sensitive world.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>ENMs as anthropogenic sources of environmental and human microbiome perturbation</title>
<p>ENMs, especially AgNPs, ZnO NPs, TiO<sub>2</sub> NPs, etc., are now ubiquitous across consumer, medical, agricultural, and industrial applications&#x2014;ranging from antimicrobial coatings and textiles to water treatment, pesticides, cosmetics, and electronics (<xref ref-type="fig" rid="F1">Figure 1</xref>). AgNPs are incorporated into food packaging materials for their antimicrobial properties, helping to extend shelf life and reduce spoilage (<xref ref-type="bibr" rid="B153">Martirosyan and Schneider, 2014</xref>). Titanium dioxide and silica (e.g., TiO<sub>2</sub>, SiO<sub>2</sub> NPs) are common food additives or colourants (for example, TiO<sub>2</sub> as food colourant E171) or anticaking agents in powdered products (<xref ref-type="bibr" rid="B253">Villamayor et al., 2023</xref>). ENMs are also used in nano-encapsulation of bioactive compounds, improving bioavailability of vitamins or nutraceuticals, and in smart packaging systems (with sensors, diffusion barriers, or controlled antimicrobial release) (<xref ref-type="bibr" rid="B153">Martirosyan and Schneider, 2014</xref>). ENMs are widely used in cosmetic formulations to improve efficacy, texture, appearance, and UV protection. Common nanomaterials include nano-TiO<sub>2</sub> and nano-zinc oxide, which serve as UV filters in sunscreens because, at the nanoscale, they offer strong UV protection while remaining transparent on skin (<xref ref-type="bibr" rid="B180">Pastrana et al., 2018</xref>; <xref ref-type="bibr" rid="B31">Catalano et al., 2021</xref>). Other ENMs include nano-silica, used to improve spreadability, reduce greasiness, act as anti-caking agents in powders and lipsticks, and enhance pigment dispersion (<xref ref-type="bibr" rid="B75">Ferreira et al., 2023</xref>). ENMs are increasingly integrated into drugs and medical products due to their unique physicochemical properties, such as high surface area, tunable size, and surface functionality. In drug and vaccine delivery, ENMs like liposomes, polymeric nanoparticles, and metal-based nanoparticles enhance bioavailability, facilitate targeted drug delivery and sustained release to specific tissues, and reduce systemic side effects. Applications of ENMs in medical devices, diagnostic imaging, wound dressings, antimicrobial textiles/implants, etc., are also increasing exponentially (<xref ref-type="bibr" rid="B29">Cai et al., 2023</xref>; <xref ref-type="bibr" rid="B129">Kurul et al., 2025</xref>); ENMs are increasingly applied in agriculture to enhance nutrient efficiency, promote plant growth, and control pests. Nano-fertilizers using metal or oxide NPs (e.g., ZnO, Fe<sub>3</sub>O<sub>4</sub>) and carrier platforms (e.g., nanoclay, chitosan) help minimize nutrient leaching and increase uptake (N, P, K) in crops (<xref ref-type="bibr" rid="B279">Yin et al., 2018</xref>). Nanopesticides formulated with ENMs offer targeted delivery, lower chemical doses, and longer persistence against pathogens (<xref ref-type="bibr" rid="B2">Adisa et al., 2019</xref>). Beyond these applications, ENMs find widespread use in general industrial sectors such as coatings, electronics, energy, and construction. TiO<sub>2</sub> NPs are used in self-cleaning and UV-resistant coatings, paints, and solar panel coatings to improve durability and reduce maintenance (<xref ref-type="bibr" rid="B161">Moloi et al., 2021</xref>; <xref ref-type="bibr" rid="B104">Hussein, 2023</xref>). Graphene, CNTs, and hybrid nanocomposites enhance electrical and thermal properties in devices, lightweight materials, and structural composites (<xref ref-type="bibr" rid="B32">Cataldi et al., 2020</xref>). Silver, zinc oxide, and silicon dioxide ENMs are used in textiles, antimicrobial surfaces, filtration systems, and sensors, due to their unique optical, catalytic or antimicrobial functionalities (<xref ref-type="bibr" rid="B161">Moloi et al., 2021</xref>; <xref ref-type="bibr" rid="B225">Singh et al., 2023</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Applications of engineered nanomaterials (ENMs), exposure pathways, and associated microbiome perturbations. The schematic tree illustrates the diverse applications of ENMs across major sectors including medicine and healthcare, water purification, food and packaging, agriculture, electronics and energy, industry, textiles, and coatings and paints. Exposure through ingestion, inhalation, dermal absorption, or soil/water contamination can disrupt human and environmental microbiomes, causing functional, compositional, and resistance-related shifts.</p>
</caption>
<graphic xlink:href="fnano-07-1666431-g001.tif">
<alt-text content-type="machine-generated">Diagram illustrating applications of nanomaterials in various sectors represented as a tree. Branches include medicine, agriculture, electronics, textiles, and more. Right side lists exposure pathways: ingestion, inhalation, dermal absorption, soil and water contamination. Microbiome perturbations like gut microbiota disruption and antimicrobial resistance are noted.</alt-text>
</graphic>
</fig>
<p>The ongoing and widespread use of ENMs brings them into frequent contact with environmental and human microbial communities, representing emerging anthropogenic sources of microbial disruption. ENMs in food (additives, packaging, nano-encapsulation), drugs or cosmetics are ingested or absorbed, while agricultural nano-fertilizers and nanopesticides enter soil and water, exposing soil and gut microbiota (<xref ref-type="bibr" rid="B113">Kah, 2015</xref>; <xref ref-type="bibr" rid="B121">Khan et al., 2021</xref>; <xref ref-type="bibr" rid="B276">Yadav et al., 2023</xref>). Improperly managed industrial nano-effluents serve as significant sources of toxicants to the environment and the food chain causing microbiome perturbations (<xref ref-type="bibr" rid="B169">Naz et al., 2024</xref>). These perturbations are dose-dependent, often manifest first in metabolic or enzymatic function and substrate utilization before major shifts in diversity or taxonomy (<xref ref-type="bibr" rid="B11">Avila-Arias et al., 2023</xref>). Given the environmental persistence and bioaccumulation potential of many ENMs, understanding realistic exposure levels (in water, soil, diet), their transformation (coating, aggregation, ion release), and their functional effects on microbial communities is critical for risk assessment and regulatory oversight.</p>
</sec>
<sec id="s3">
<label>3</label>
<title>ENMs and human microbiome</title>
<p>The human gut microbiota is a complex community of trillions of microorganisms, primarily bacteria that live in the gastrointestinal tract, especially the colon. These microbes play a crucial role in maintaining human health by aiding in digestion, synthesizing essential vitamins, regulating the immune system, and protecting against harmful pathogens. The composition of the gut microbiota is influenced by various factors, including diet, antibiotics, age, and lifestyle. A balanced microbiota supports overall health, while disruptions, known as dysbiosis, have been linked to numerous conditions such as inflammatory bowel disease, obesity, diabetes, and mental health disorders (<xref ref-type="bibr" rid="B239">Thursby and Juge, 2017</xref>; <xref ref-type="bibr" rid="B102">Hou et al., 2022</xref>). ENMs, such as Ag NPs, TiO<sub>2</sub> NPs, ZnO NPs, and CNMs are increasingly used in food additives, packaging, pharmaceuticals, and cosmetics. When ingested, either directly through food or indirectly <italic>via</italic> environmental exposure, these NMs can interact with the gut microbiota and potentially disrupt gut health. Studies have shown that certain ENMs can alter the composition and diversity of the microbial community, leading to dysbiosis, inflammation, and impaired gut barrier function (<xref ref-type="bibr" rid="B246">Utembe et al., 2022</xref>). For example, Ag NPs and TiO<sub>2</sub> NPs have been associated with reduced beneficial bacteria (like <italic>Lactobacillus</italic> and <italic>Bifidobacterium</italic>) and increased pro-inflammatory species (<xref ref-type="bibr" rid="B246">Utembe et al., 2022</xref>; <xref ref-type="bibr" rid="B149">Ma Y. et al., 2023</xref>). Additionally, ENMs can affect microbial metabolism and the production of SCFAs, which are vital for maintaining intestinal health (<xref ref-type="fig" rid="F2">Figure 2</xref>). While the long-term impacts on human health are still being investigated, emerging evidence suggests that chronic exposure to ENMs may contribute to gastrointestinal disorders, immune dysregulation, and metabolic disturbances by disrupting the delicate balance of the gut ecosystem (<xref ref-type="table" rid="T1">Table 1</xref>) (<xref ref-type="bibr" rid="B235">Tang et al., 2021</xref>; <xref ref-type="bibr" rid="B263">Wojciechowska et al., 2023</xref>).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Effects of engineered nanomaterials (ENMs) on human gut microbiota and environmental microbial communities. This schematic illustrates the multifaceted impacts of ENMs, including metal-based nanoparticles and carbon nanomaterials, on microbial ecosystems. In the human gut, ENMs disrupt microbial diversity and composition, reducing beneficial taxa, altering short-chain fatty acid (SCFA) production, and compromising gut barrier integrity, which may lead to dysbiosis, inflammation, and metabolic disorders. In environmental systems (aquatic, soil, and agricultural), ENMs interfere with microbial-mediated biogeochemical processes such as nitrogen fixation, denitrification, and organic matter decomposition, potentially impairing nutrient cycling and ecosystem resilience.</p>
</caption>
<graphic xlink:href="fnano-07-1666431-g002.tif">
<alt-text content-type="machine-generated">Illustration showing the impact of engineered nanomaterials on gut microbiome and intestinal health. Arrows indicate pathways: interaction through medicines, diet, and environmental factors, and exposure via industrial effluents and carbon nanomaterials. Disruption in short-chain fatty acid (SCFA) production and creation of an immunoreactive micro-environment lead to gut dysbiosis, cytotoxicity, and genotoxicity. Effects include impaired microbiome enzyme activities, reduced biofilm biomass, disrupted nutrient cycling, and threats to agricultural productivity and environmental stability.</alt-text>
</graphic>
</fig>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Effects of Engineered Nanomaterials (ENMs) on the human microbiota.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Nano-materials</th>
<th align="left">Effects on microbiota</th>
<th align="left">Mechanisms of action</th>
<th align="left">Health implications</th>
<th align="left">Key references</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">TiO<sub>2</sub> NPs</td>
<td align="left">Altered specific bacterial groups, i.e., <italic>Lactobacillus</italic>, <italic>Firmicutes</italic>, <italic>Proteobacteria</italic>, etc., leading to dysbiosis, hindered the growth of beneficial bacteria like <italic>Lactobacillus</italic> and <italic>Bifidobacterium</italic>
</td>
<td align="left">
<italic>In vitro</italic> alteration of tryptophan and arginine metabolism; <italic>in vivo</italic> downregulation of neuroprotective metabolites in urine; metabolic reprogramming</td>
<td align="left">Gut dysbiosis; disrupted microbial-host metabolic signaling</td>
<td align="left">
<xref ref-type="bibr" rid="B266">Wu et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">TiO<sub>2</sub>-, Ag-, SiO<sub>2</sub>-, iron oxides, ZnO- NPs</td>
<td align="left">Exposure through food additive alters microbial composition; disrupts gut barrier; antimicrobial shifts; reduces commensals</td>
<td align="left">Oxidative stress, barrier dysfunction, antimicrobial action</td>
<td align="left">Colitis, obesity, immune dysfunction, metabolic shifts</td>
<td align="left">
<xref ref-type="bibr" rid="B81">Gangadoo et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">AgNPs</td>
<td align="left">Oral exposure altered gut microbiota composition: Decreases microbes in energy, amino acid, lipid metabolism</td>
<td align="left">Ag accumulation; altered amino acid, purine, pyrimidine, lipid and energy metabolism</td>
<td align="left">Dysbiosis- liver metabolic linkage; &#x223c;23% microbial shifts correlated with &#x223c;60% metabolite changes</td>
<td align="left">
<xref ref-type="bibr" rid="B257">Wang et al. (2022)</xref>
</td>
</tr>
<tr>
<td align="left">ZnO NPs</td>
<td align="left">Alteration in microbial richness and diversity based on pre-existing health condition; alterations in plasma metabolites, indicating a complex and systemic metabolic impact; reduced SCFAs</td>
<td align="left">Antibacterial activity, modulation of Nrf2 pathway, dose-dependent effects</td>
<td align="left">Gut dysbiosis, immune effects, context-specific benefits</td>
<td align="left">
<xref ref-type="bibr" rid="B281">Yu et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">CNMs (graphene, CNTs)</td>
<td align="left">Affect microbial fermentation altering the production of key metabolites such as butyrate, inhibit probiotics whereas promoting the growth of opportunistic pathogens</td>
<td align="left">Used as carbon source, fermentation into butyrate, oxidative stress</td>
<td align="left">Gut dysbiosis, altered proliferation and differentiation of intestinal stem cells, long-term gut risks</td>
<td align="left">
<xref ref-type="bibr" rid="B49">Cui et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">AgNPs</td>
<td align="left">Airway inhalation altered airway microbiome; innate immune activation</td>
<td align="left">Transcriptomic profiling showed upregulated innate immune pathways</td>
<td align="left">Potential airway inflammation, dysbiosis-linked immune modulation</td>
<td align="left">
<xref ref-type="bibr" rid="B298">Zickgraf et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Carbon black &#x2b; ozone</td>
<td align="left">Amplified bacterial load in the gut, i.e., <italic>Firmicutes</italic>, <italic>Bacteroidetes</italic>&#xa0;and <italic>Lactobacillus</italic> along with decreased <italic>Clostridiaceae</italic>
</td>
<td align="left">Oxidative stress and immune&#x2013;microbiome interaction</td>
<td align="left">Gut dysbiosis, shifts in gut-lung axis balance</td>
<td align="left">
<xref ref-type="bibr" rid="B298">Zickgraf et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Ag-, SiO<sub>2</sub>-, Ti-, TiO<sub>2</sub>- NPs</td>
<td align="left">Alteration in mollicutes, reduction in <italic>Proteobacteria</italic>, <italic>Deltaproteobacteria</italic>, and <italic>Desulfovibrionales</italic>; decreased the relative abundance of Eggerthellaceae family in gut microbiota</td>
<td align="left">Downregulation of inflammatory cytokines in jejunum; modulation of cytokine and alarmin expressionin organoids</td>
<td align="left">Micro-inflammation; increased susceptibility to dextran sodium sulfate-induced colitis; potential aggravation of inflammatory bowel disease (IBD)and immune-mediated disorders</td>
<td align="left">
<xref ref-type="bibr" rid="B90">Guilloteau et al. (2022)</xref>
</td>
</tr>
<tr>
<td align="left">AgNPs and silver nanowires</td>
<td align="left">Inhibiting the proliferation of Gram-negative bacteriaand lessening the gut microbiotadiversity in mice after short-term (14 days) exposure</td>
<td align="left">Enhanced 1H-indole-3-carboxylic acid and elevated levels of 5-HT in the gut and blood, oxidative stress, DNA damage, lipid peroxidation</td>
<td align="left">Persistent metabolic reprogramming despite microbial recovery; potential risks for gut&#x2013;brain axis modulation, dysbiosis, irritable bowel syndrome, inflammatory bowel disease, liver metabolic disruption</td>
<td align="left">
<xref ref-type="bibr" rid="B259">Wang X. et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">ZnO NPs (25&#x2013;100&#xa0;mg/kg in hens, 9 weeks)</td>
<td align="left">Dose-dependent reduction in microbiota richness; altered community structure (<italic>Bacilli, Fusobacteria, Proteobacteria</italic>); reduced <italic>Lactobacillus</italic> abundance</td>
<td align="left">Disruption of gut microbial community balance; altered metabolism of glucose, amino acids; choline, lactate, methionine positively correlated with richness</td>
<td align="left">Potential dysbiosis at higher doses; disturbance in nutrient metabolism, such as glucose, amino acids; links between reduced bacterial richness and metabolic imbalance</td>
<td align="left">
<xref ref-type="bibr" rid="B74">Feng et al. (2017)</xref>
</td>
</tr>
<tr>
<td align="left">TiO<sub>2</sub> NPs</td>
<td align="left">Cytotoxicity, developmental alterations; immune response modulation in humans, mice, zebrafish, nematodes, plants</td>
<td align="left">Changes in gene expression linked to stress, immune pathways, development; effects depend on intrinsic and transformed particle properties</td>
<td align="left">Potential risks to gut and immune health; disruption of developmental and metabolic pathways</td>
<td align="left">
<xref ref-type="bibr" rid="B299">Wang S. et al. (2022)</xref>
</td>
</tr>
<tr>
<td align="left">ZnO NPs</td>
<td align="left">Cytotoxicity and immune modulation<break/>- Developmental changes in model organisms</td>
<td align="left">Transcriptomic signatures of oxidative stress, apoptosis, inflammation<break/>- Influenced by particle surface chemistry and transformations</td>
<td align="left">Risks of cytotoxicity and immune dysregulation in humans<break/>- Possible contribution to inflammatory conditions</td>
<td align="left">
<xref ref-type="bibr" rid="B299">Wang S. et al. (2022)</xref>
</td>
</tr>
<tr>
<td align="left">Nano-ZnO, 0.1&#x2013;2.5&#xa0;mg/L, <italic>in vitro</italic> colon simulator</td>
<td align="left">Dose-dependent downregulation of microbiota diversity; altered community composition; reduction in SCFA production; shifts in functional metabolic pathways; alteration in antibiotic resistance genes (ARGs)</td>
<td align="left">Direct toxicity to gut bacteria, altering growth and functional pathways; disruption of fermentation processes lowering SCFA levels; modulation of gut resistome through selective bacterial inhibition or enrichment</td>
<td align="left">Reduced SCFA production may impair gut barrier and metabolic health; enrichment of ARGs at low dose raises risk of antimicrobial resistance; indicates potential long-term risks for gut health</td>
<td align="left">
<xref ref-type="bibr" rid="B289">Zhang et al. (2021)</xref>
</td>
</tr>
</tbody>
</table>
</table-wrap>
<sec id="s3-1">
<label>3.1</label>
<title>Impact of titanium dioxide nanoparticles on gut microbiota and their mechanism of interaction</title>
<p>TiO<sub>2</sub> NPs appear to exert a limited effect on gut microbiota diversity; however, they tend to influence the overall abundance of gut bacteria more noticeably (<xref ref-type="table" rid="T1">Table 1</xref>). Notably, TiO<sub>2</sub> NPs have been found to affect specific bacterial groups, including <italic>Lactobacillus</italic>, as well as members of the <italic>Firmicutes</italic> and <italic>Proteobacteria</italic> phyla, while leaving overall microbial diversity at higher taxonomic levels relatively unaffected (<xref ref-type="bibr" rid="B142">Lin et al., 2014</xref>; <xref ref-type="bibr" rid="B227">Sohm et al., 2015</xref>; <xref ref-type="bibr" rid="B27">Burke et al., 2015</xref>; <xref ref-type="bibr" rid="B290">Zhang et al., 2022</xref>; <xref ref-type="bibr" rid="B149">Ma Y. et al., 2023</xref>). For instance, a total of 42 bacterial species were reported to undergo significant changes upon TiO<sub>2</sub> NPs exposure, suggesting a risk of dysbiosis (<xref ref-type="bibr" rid="B290">Zhang et al., 2022</xref>). These compositional shifts are accompanied by disruptions in key metabolic pathways, particularly those associated with oxidative phosphorylation and energy metabolism, which are critical for maintaining gut health (<xref ref-type="fig" rid="F2">Figure 2</xref>). <italic>In vitro</italic> studies also indicated that TiO<sub>2</sub> NPs can inhibit the growth of beneficial bacteria like <italic>Lactobacillus</italic> and <italic>Bifidobacterium</italic>, through an exposure of diets containing 0.1% TiO<sub>2</sub> NPs for 90&#xa0;days to 1&#xa0;mg/kg TiO2 NP for 7&#xa0;days respectively, further implicating them in adverse gut effects (<xref ref-type="bibr" rid="B266">Wu et al., 2023</xref>). Such microbial disturbances have been associated with health risks, including colitis and obesity (<xref ref-type="bibr" rid="B81">Gangadoo et al., 2021</xref>). Although some evidence suggests that TiO<sub>2</sub> NPs might enhance probiotic diversity under certain conditions, the prevailing data highlight their potential to negatively impact gut microbial communities (<xref ref-type="bibr" rid="B127">Kumar A. et al., 2024</xref>). Notably, these effects appear to be dose- and duration-dependent, underscoring the need for more comprehensive research to clarify the complex interactions between TiO<sub>2</sub> NPs and the gut microbiome.</p>
<p>TiO<sub>2</sub> NPs interact with gut microbiota primarily through mechanisms that induce dysbiosis linked to various health disorders, inflammation, immune modulation, and metabolic pathway disruption (<xref ref-type="fig" rid="F2">Figure 2</xref>). Studies have shown that oral exposure to TiO<sub>2</sub> NPs leads to significant shifts in microbial composition; for instance, decreasing beneficial bacteria like <italic>Veillonella</italic> while increasing genera such as <italic>Lactobacillus gasseri</italic>, <italic>Turicibacter</italic>, <italic>Lachnospiraceae</italic> NK4A136 group, etc., thereby impairing normal gut function and metabolism (<xref ref-type="bibr" rid="B37">Chen et al., 2019</xref>; <xref ref-type="bibr" rid="B277">Yan et al., 2020</xref>; <xref ref-type="bibr" rid="B204">Rinninella et al., 2021</xref>; <xref ref-type="bibr" rid="B21">Bianchi et al., 2024</xref>). These NPs also induce ROS within the gut, causing oxidative stress and inflammation that facilitate lipopolysaccharide (LPS) leakage from Gram-negative bacteria, further exacerbating gut inflammation-a process implicated in chronic metabolic diseases like obesity and diabetes. Additionally, TiO<sub>2</sub> NPs may directly engage with intestinal immune cells, altering the microbiota&#x2013;immune system axis and perpetuating inflammatory responses (<xref ref-type="bibr" rid="B132">Lamas et al., 2023</xref>). Metabolically, TiO<sub>2</sub> NP exposure disrupts critical bacterial pathways including energy metabolism, detoxification, amino acid metabolism and SCFA production, which are vital for maintaining gut barrier integrity and regulating host energy homeostasis (<xref ref-type="bibr" rid="B246">Utembe et al., 2022</xref>; <xref ref-type="bibr" rid="B266">Wu et al., 2023</xref>; <xref ref-type="bibr" rid="B189">Pinget et al., 2019</xref>; <xref ref-type="bibr" rid="B278">Yang et al., 2022</xref>). Liquid chromatography-mass spectrometry (LC-MS/MS)-based untargeted metabolomics analysis demonstrated that TiO<sub>2</sub> NPs disrupt critical metabolic pathways in gut bacteria, particularly tryptophan and arginine metabolism, which are essential for maintaining gut and host health. <italic>In vivo</italic> studies showed that mice fed a diet containing TiO<sub>2</sub> NPs (0.1&#xa0;wt% for 8&#xa0;weeks) exhibited significant changes in urinary metabolites, with notable alterations in the tryptophan metabolism pathway. Furthermore, different neuroprotective metabolites such as tryptamine, N-Methyltryptamine, 6-Hydroxymelatonin, and N-Acetylserotonin, were significantly decreased in both bacterial cultures and the urine of treated mice (<xref ref-type="bibr" rid="B266">Wu et al., 2023</xref>). These interlinked mechanisms, i.e., microbial imbalance, oxidative-inflammation signaling, immune dysregulation, and metabolic impairment highlight how TiO<sub>2</sub> NPs can detrimentally reshape the gut ecosystem and contribute to metabolic health disturbances.</p>
<p>The interactions between NPs and gastrointestinal microbiota are governed by multiple parameters, including the surface charge and physicochemical properties of both NPs and bacterial cells, the electrostatic interactions with digested food matrices, the chemical composition and bioactivity of dietary components, as well as dynamic physicochemical conditions within the gastrointestinal tract, such as pH gradients, enzymatic activity, ionic strength, and the presence of bile salts and other metabolites (<xref ref-type="bibr" rid="B222">Siemer et al., 2018</xref>; <xref ref-type="bibr" rid="B16">Baranowska-W&#xf3;jcik, 2021</xref>). Analysis of the impact of engineered NPs on both commensal and pathogenic microorganisms in a gastrointestinal study showed that food-grade and model NPs readily form stable complexes with both probiotic and pathogenic bacteria under simulated gastrointestinal conditions. NP size emerged as the key determinant of NP&#x2013;bacteria interactions, with smaller negatively charged NPs binding more efficiently to bacterial surfaces than larger positively charged ones, regardless of charge similarity. Additionally, low gastric pH enhanced complexation, while polymer coatings on NPs inhibited binding <italic>via</italic> steric repulsion, highlighting factors influencing NP&#x2013;microbe interactions in the GI tract (<xref ref-type="bibr" rid="B222">Siemer et al., 2018</xref>). Toxicity analysis of five TiO<sub>2</sub> NPs (10&#x2013;50&#xa0;nm) with different crystal phases using <italic>Escherichia coli</italic> revealed that antibacterial activity decreased with larger particle size and higher rutile content. Smaller anatase TiO<sub>2</sub> NPs induced greater ROS production, membrane damage, and internalization, while higher pH and ionic strength reduced their antibacterial efficacy (<xref ref-type="bibr" rid="B142">Lin et al., 2014</xref>). Further, it has been reported that oral TiO<sub>2</sub> NPs aggravated acute colitis by activating the NLRP3 inflammasome, leading to IL-1&#x3b2; and IL-18 release, ROS generation, and increased intestinal permeability. TiO<sub>2</sub> crystals accumulated in the spleen of treated mice, and elevated titanium levels were detected in UC patients with active disease (<xref ref-type="bibr" rid="B209">Ruiz et al., 2017</xref>). These findings suggest potential harm of TiO<sub>2</sub> NPs in individuals with compromised gut barrier and pre-existing inflammation, like IBD.</p>
</sec>
<sec id="s3-2">
<label>3.2</label>
<title>AgNPs and gut microbiota: exploring their impact and interaction mechanisms</title>
<p>The impacts of AgNPs on the human gut microbiota are complex and multifaceted, involving direct antimicrobial activity, disruption of microbial community structure, modulation of host metabolism, and impairment of gut barrier integrity (<xref ref-type="table" rid="T1">Table 1</xref>). AgNPs exert direct antimicrobial effects by interacting with bacterial cells, where they damage cell membranes, interfere with metabolic pathways, and inhibit DNA replication, ultimately leading to bacterial death (<xref ref-type="bibr" rid="B26">Bruna et al., 2021</xref>; <xref ref-type="bibr" rid="B207">Rodrigues et al., 2024</xref>). A key mechanism underlying these effects is the induction of oxidative stress within gut bacteria, characterized by increased nitric oxide production, lipid peroxidation, and DNA damage, all of which can destabilize the gut microbial ecosystem and promote dysbiosis (<xref ref-type="bibr" rid="B136">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B1">Adeyemi et al., 2020</xref>; <xref ref-type="bibr" rid="B151">Manuja et al., 2021</xref>).</p>
<p>Such antimicrobial actions lead to significant alterations in the structural composition of the gut microbiota, with notable shifts in community diversity and abundance (<xref ref-type="fig" rid="F2">Figure 2</xref>). AgNPs have been shown to selectively inhibit the growth of certain Gram-negative bacteria, reducing the prevalence of beneficial taxa like <italic>Bacteroides</italic> while favoring opportunistic and potentially pathogenic groups such as <italic>Enterococcus</italic> (<xref ref-type="bibr" rid="B162">More et al., 2023</xref>; <xref ref-type="bibr" rid="B270">Xie et al., 2023</xref>). These compositional changes result in a measurable loss of microbial diversity, particularly after short-term AgNP exposure (<xref ref-type="bibr" rid="B20">Bi et al., 2020</xref>; <xref ref-type="bibr" rid="B259">Wang X. et al., 2023</xref>). This loss of diversity has been directly associated with dysbiosis and adverse health outcomes, including gastrointestinal disorders (<xref ref-type="bibr" rid="B86">Ghebretatios et al., 2021</xref>). Interestingly, some studies suggest that microbial diversity may partially recover over extended exposure periods; however, metabolic perturbations often persist, indicating enduring effects on host physiology (<xref ref-type="bibr" rid="B259">Wang X. et al., 2023</xref>). Structural alterations are particularly prominent among microorganisms involved in energy, amino acid, and lipid metabolism (<xref ref-type="bibr" rid="B257">Wang, X. et al., 2022</xref>). Notably, in studies where mice received oral gavage of AgNPs once daily for 120 consecutive days, there were significant alterations in gut microbial functions associated with amino acid, purine, pyrimidine, lipid, and energy metabolism, as well as downstream effects on liver metabolic pathways (<xref ref-type="bibr" rid="B257">Wang, X. et al., 2022</xref>). Further, AgNPs significantly impact bacterial adhesion to the intestinal epithelium, a critical step in colonization and biofilm development. AgNPs exert a dual role in adhesion dynamics&#x2014;primarily inhibiting bacterial attachment and biofilm formation, yet potentially triggering compensatory virulent behaviors under certain conditions. These adhesion-disrupting effects are crucial for their application in gut environments, where they may influence both pathogen colonization and commensal biofilm stability (<xref ref-type="bibr" rid="B211">Saeki et al., 2021</xref>; <xref ref-type="bibr" rid="B3">Afrasiabi and Partoazar, 2024</xref>; <xref ref-type="bibr" rid="B88">Gonz&#xe1;lez-Fern&#xe1;ndez et al., 2025</xref>).</p>
<p>Moreover, AgNPs can compromise the integrity of the intestinal barrier, which serves as a critical defense against the translocation of bacteria and toxins from the gut lumen into the systemic circulation (<xref ref-type="fig" rid="F2">Figure 2</xref>). Disruption of this barrier has been linked to increased gut permeability, low-grade inflammation, and the potential development of systemic health issues (<xref ref-type="bibr" rid="B219">Shayo et al., 2024</xref>; <xref ref-type="bibr" rid="B138">Li W. et al., 2024</xref>). While AgNPs hold promise in controlling pathogenic bacteria, their ability to perturb microbial balance and host metabolic processes raises significant concerns regarding their widespread use in consumer products and medical applications. The inherent resilience of the gut microbiome may offer some degree of recovery from AgNP-induced dysbiosis; however, the persistence of metabolic and barrier-related disruptions highlights the need for cautious evaluation of AgNP exposure and its long-term implications for gut and overall health.</p>
<p>The biological impact of AgNPs on gut microbiota is strongly shaped by particle size, shape, surface charge, concentration, surface coating, and the existing microbial community. Smaller AgNPs (&#x3c;10&#xa0;nm) exhibit heightened toxicity due to their larger surface-area-to-volume ratios, accelerated release of Ag<sup>&#x2b;</sup> ions, and greater ROS generation, which promotes oxidative stress in microbial cells (<xref ref-type="bibr" rid="B292">Zhang L. et al., 2018</xref>; <xref ref-type="bibr" rid="B157">Menichetti et al., 2023</xref>; <xref ref-type="bibr" rid="B60">Din&#xe7;, 2025</xref>; <xref ref-type="bibr" rid="B214">Sati et al., 2025</xref>). NP shape also affects efficacy; spherical, triangular, hexagonal, cubic or rod-shaped forms of AgNPs displayed variable antimicrobial activity. However, the anti-microbial potential based upon morphological attributes varied contrastingly according to the variable experimental conditions (<xref ref-type="bibr" rid="B250">Van Dong et al., 2012</xref>; <xref ref-type="bibr" rid="B6">Alshareef et al., 2017</xref>; <xref ref-type="bibr" rid="B94">Hanan et al., 2018</xref>; <xref ref-type="bibr" rid="B251">Vanlalveni et al., 2024</xref>). Therefore, a generalization may draw false narrative. Surface charge modulates interactions with bacteria: positively charged AgNPs strongly adhere to negatively charged bacterial membranes <italic>via</italic> electrostatic attraction, increasing membrane disruption and antimicrobial potency, whereas negatively charged or neutral coatings can reduce this effect (<xref ref-type="bibr" rid="B68">El Badawy et al., 2011</xref>; <xref ref-type="bibr" rid="B6">Alshareef et al., 2017</xref>). The concentration of AgNPs is critical&#x2014;higher doses induce more pronounced disturbances in microbial diversity, metabolic function, and intestinal inflammation, while low or sub-threshold levels may have minimal or reversible effects; for instance, a dose-dependent alteration in gut microbiota &#x3b1;- and &#x3b2;-diversity has been reported in mice orally exposed for 28&#xa0;days to food pellets supplemented with increasing doses of AgNPs (0, 46, 460, or 4,600&#xa0;ppb). They also observed that higher doses shifted the phyla balance (<italic>Firmicutes vs.</italic> <italic>Bacteroidetes</italic>), but low doses had lesser or no overt toxicity (<xref ref-type="bibr" rid="B249">van Den Brule et al., 2015</xref>). Similarly, oral exposure to AgNPs (0, 1, 5, 10, 25, 50&#xa0;mg/kg&#xa0;bw/day for 4&#xa0;weeks) induced dose-dependent toxicity in mice, evidenced by body weight suppression and reduced intestinal dendritic cell numbers, confirming that both systemic and local immune effects scale with dose (<xref ref-type="bibr" rid="B201">Ren et al., 2023</xref>). However, contrasting results have also been reported documenting no changes in the <italic>Firmicutes/Bacteroidetes</italic> ratio in gut microbiota of rats and mice exposed to AgNPs at dose levels of 9&#xa0;mg/kg&#xa0;bw/day and 10&#xa0;mg/kg&#xa0;bw/day, respectively (<xref ref-type="bibr" rid="B262">Wilding et al., 2016</xref>; <xref ref-type="bibr" rid="B92">Hadrup et al., 2012</xref>). The duration of NP exposure may also have significant effects. In mice, administration of AgNPs and Ag nanowires (0.5 and 2.5&#xa0;mg/kg) for 14&#xa0;days reduced gut microbial diversity and altered community structure. After 28&#xa0;days, partial recovery of the microbiota was observed, although metabolic disturbances, particularly in gut metabolites, persisted (<xref ref-type="bibr" rid="B259">Wang X. et al., 2023</xref>). Surface coatings, such as PEG, PVP, or chitosan, are routinely used to reduce toxicity by limiting dissolution and aggregation; PEG-coated AgNPs, for instance, exhibit reduced cytotoxicity and attenuated gut microbiota disruption (<xref ref-type="bibr" rid="B28">Caballero-D&#xed;azet al., 2013</xref>; <xref ref-type="bibr" rid="B52">Das et al., 2017</xref>; <xref ref-type="bibr" rid="B157">Menichetti et al., 2023</xref>; <xref ref-type="bibr" rid="B251">Vanlalveni et al., 2024</xref>). Finally, the baseline gut microbiota composition and host factors shape the response to AgNPs exposure&#x2014;individual differences in microbial communities, and host-specific parameters determine susceptibility to dysbiosis and ecological shifts (<xref ref-type="bibr" rid="B201">Ren et al., 2023</xref>). Even, AgNPs exposure during critical developmental periods leads to enduring gut dysbiosis, neurobehavioral, and metabolic alterations as evidenced in mice (<xref ref-type="bibr" rid="B145">Lyu et al., 2021</xref>). Together, these factors underscore that the effects of AgNPs on gut health are not solely dependent on dosage but are the result of complex nanoparticle&#x2013;microbiome interactions that must be addressed in designing safe, targeted applications.</p>
</sec>
<sec id="s3-3">
<label>3.3</label>
<title>ZnO NPs and gut microbiota dynamics</title>
<p>ZnO NPs exert multifaceted effects on the human gut microbiota, influencing microbial diversity, community composition, and metabolic activity (<xref ref-type="table" rid="T1">Table 1</xref>) (<xref ref-type="fig" rid="F2">Figure 2</xref>). Research shows that these effects are highly dependent on factors such as concentration and the individual&#x2019;s health status. For example, ZnO NPs [0&#xa0;mg/kg (control), 25&#xa0;mg/kg, 50&#xa0;mg/kg, and 100&#xa0;mg/kg] were fed to poultry birds for 9&#xa0;weeks; at the highest concentration (100&#xa0;mg/kg), ZnO NPs tended to reduce microbial richness and diversity, particularly impacting beneficial bacteria such as <italic>Lactobacillus</italic> (<xref ref-type="bibr" rid="B74">Feng et al., 2017</xref>). Exposure of the human intestinal microbiome to ZnO NPs at 0.1, 2.5, and 50&#xa0;mg/L revealed clear dose-dependent effects. While low concentrations caused minimal changes, higher doses (especially 50&#xa0;mg/L) significantly altered microbial composition, reduced diversity, and disrupted metabolic functions (<xref ref-type="bibr" rid="B289">Zhang et al., 2021</xref>). However, the response is not uniform across all populations. In children with Autism Spectrum Disorder, ZnO NPs actually increased gut bacterial diversity, whereas a decrease was observed in healthy children, suggesting that pre-existing health conditions may modulate the microbial response to ZnO NP exposure (<xref ref-type="bibr" rid="B281">Yu et al., 2021</xref>). Metabolically, ZnO NPs have been associated with a reduction in the production of SCFAs, which play essential roles in gut health and host metabolism (<xref ref-type="bibr" rid="B289">Zhang et al., 2021</xref>). Additionally, alterations in gut microbiota composition due to ZnO NPs have been linked to changes in plasma metabolites, indicating a complex and systemic metabolic impact (<xref ref-type="bibr" rid="B74">Feng et al., 2017</xref>). The effects of ZnO NPs also extend to microbial resistance traits. While medium concentrations were shown to reduce antibiotic resistance genes, low concentrations paradoxically enriched tetracycline resistance genes, revealing a nuanced influence on the gut resistome (<xref ref-type="bibr" rid="B289">Zhang et al., 2021</xref>). Interestingly, not all effects of ZnO NPs are negative. In certain contexts, such as in broiler chickens, ZnO NPs have been found to support the growth of beneficial bacteria, enhance gut health, and boost immune function (<xref ref-type="bibr" rid="B194">Qu et al., 2023</xref>). This duality highlights the complexity of ZnO NP interactions with the gut microbiome and underscores the need for further targeted studies to fully elucidate their health implications.</p>
<p>ZnO NPs influence gut microbiota through several mechanisms of action, with their effects varying depending on individual health status, such as in children with Attention-Deficit Hyperactivity Disorder or Autism Spectrum Disorder, as well as in various animal models. One of the primary mechanisms is their antibacterial activity. ZnO NPs have been shown to inhibit the growth of gut bacteria, particularly in healthy children, where they significantly reduced the number of live bacterial cells (<xref ref-type="bibr" rid="B296">Zhou et al., 2021</xref>; <xref ref-type="bibr" rid="B281">Yu et al., 2021</xref>). However, this response appears to differ in children with ASD, where ZnO NP exposure was associated with an increase in gut bacterial diversity, suggesting a more complex interaction with pre-existing microbial communities (<xref ref-type="bibr" rid="B281">Yu et al., 2021</xref>). Additionally, ZnO NPs are known to modulate microbial diversity by altering the overall community structure of gut bacteria. Higher concentrations, particularly 100&#xa0;mg/kg, orally, for 9&#xa0;days have been linked to a notable decline in beneficial bacteria such as <italic>Lactobacillus</italic> in poultry birds, with bacterial richness showing a negative correlation with ZnO NPs concentration indicating that excessive exposure may contribute to gut dysbiosis (<xref ref-type="bibr" rid="B74">Feng et al., 2017</xref>). Beyond their antimicrobial properties, ZnO NPs also possess anti-inflammatory effects. In conditions such as ulcerative colitis, they have been reported to help restore gut homeostasis by activating the Nrf2 signaling pathway and reducing levels of pro-inflammatory cytokines (<xref ref-type="bibr" rid="B135">Li et al., 2017</xref>). These findings suggest that while ZnO NPs can beneficially modulate gut microbiota and reduce inflammation under certain conditions, their overuse or inappropriate application may lead to harmful effects. Therefore, careful consideration of dosage and individual health status is essential when evaluating the therapeutic or dietary use of ZnO nanoparticles.</p>
</sec>
<sec id="s3-4">
<label>3.4</label>
<title>Carbon nanomaterials-gut microbiota interaction</title>
<p>CNMs, including single-walled carbon nanotubes (SWCNTs) and graphene oxide (GO), CNM-based nanozymes, quantum dots have a significant and multifaceted impact on the human gut microbiota, influencing both microbial composition and metabolic processes (<xref ref-type="table" rid="T1">Table 1</xref>) (<xref ref-type="bibr" rid="B14">Bantun et al., 2022</xref>; <xref ref-type="bibr" rid="B294">Zhao et al., 2024</xref>). These materials become integrated into the gut&#x2019;s carbon flow, where they affect microbial fermentation and alter the production of key metabolites such as butyrate (<xref ref-type="bibr" rid="B49">Cui et al., 2023</xref>). This interaction has the potential to influence the proliferation and differentiation of intestinal stem cells, raising concerns about the possible health risks associated with CNM exposure. One major impact of CNMs is on the microbial composition within the gut. Studies in rodents show that single-walled CNTs and GO, when ingested, alter microbial composition shifting the <italic>Firmicutes/Bacteroidetes</italic> balance and increasing pro-inflammatory taxa like <italic>Alistipes</italic> and <italic>Lachnospiraceae</italic> (<xref ref-type="bibr" rid="B36">Chen et al., 2018</xref>; <xref ref-type="bibr" rid="B246">Utembe et al., 2022</xref>). CNM exposure can inhibit the growth of beneficial probiotic bacteria while promoting the growth of opportunistic pathogens, leading to dysbiosis (<xref ref-type="fig" rid="F2">Figure 2</xref>) (<xref ref-type="bibr" rid="B149">Ma Y. et al., 2023</xref>; <xref ref-type="bibr" rid="B263">Wojciechowska et al., 2023</xref>; <xref ref-type="bibr" rid="B39">Chen et al., 2025</xref>). Interestingly, CNMs may also lead to an increase in butyrate-producing bacteria, as some of these microbes can utilize CNMs as a carbon source. This shift in population dynamics can have downstream effects on gut health and homeostasis (<xref ref-type="bibr" rid="B49">Cui et al., 2023</xref>). Beyond compositional changes, CNMs also influence gut microbial metabolism. Through fermentation, CNMs are converted into organic metabolites such as butyrate, which plays a critical role in gut physiology. However, the excessive production of butyrate due to CNM metabolism can disrupt normal intestinal processes by affecting the proliferation and differentiation of intestinal stem cells (<xref ref-type="bibr" rid="B49">Cui et al., 2023</xref>). These metabolic shifts could have long-term implications for intestinal function and overall health. Although the adverse effects of CNMs on gut microbiota are becoming increasingly evident, the broader implications for human health are still being explored. Responses to CNM exposure appear to vary among individuals, likely due to differences in baseline microbiota composition and genetic predispositions. Therefore, more comprehensive research is necessary to understand the full scope of health risks and to identify potential strategies for mitigating the negative effects of CNMs on the gut microbiome (<xref ref-type="bibr" rid="B263">Wojciechowska et al., 2023</xref>; <xref ref-type="bibr" rid="B298">Zickgraf et al., 2023</xref>; <xref ref-type="bibr" rid="B39">Chen et al., 2025</xref>).</p>
<p>The mechanisms through which CNMs affect the human gut microbiome are complex, involving both direct interactions with microbial populations and indirect influences <italic>via</italic> metabolic pathways. Recent research has shown that CNMs, such as single-walled carbon nanotubes and GO, can be utilized by gut microbiota as a novel carbon source. This fermentation process results in the production of beneficial metabolites such as butyrate, a SCFA, essential for gut health and the regulation of intestinal cellular functions (<xref ref-type="bibr" rid="B49">Cui et al., 2023</xref>). CNMs enhance microbial fermentation by selectively supporting the growth of specific butyrate-producing bacteria, thereby increasing butyrate levels in the gut. This has important implications for maintaining intestinal health and promoting epithelial integrity (<xref ref-type="bibr" rid="B49">Cui et al., 2023</xref>). However, the impact of CNMs on microbial metabolism is concentration-dependent. While moderate levels may support SCFA production, high concentrations of CNMs can suppress key metabolic pathways, disrupting SCFA synthesis and potentially leading to adverse physiological outcomes (<xref ref-type="fig" rid="F2">Figure 2</xref>) (<xref ref-type="bibr" rid="B49">Cui et al., 2023</xref>; <xref ref-type="bibr" rid="B263">Wojciechowska et al., 2023</xref>). In addition to their metabolic effects, CNMs possess antimicrobial properties. They can compromise microbial cell integrity through oxidative stress, membrane disruption, and other toxic effects. The antimicrobial efficacy of CNMs including GO, CNTs, fullerenes, and carbon quantum dots is strongly governed by their physical and chemical attributes: size, shape, and surface functionalization. (<xref ref-type="bibr" rid="B150">Maksimova, 2019</xref>). Smaller GO sheets, for instance, exhibit higher oxidative stress&#x2013;mediated killing when used as surface coatings, while larger sheets in suspension are more effective at entrapping and isolating bacteria, with smaller ones (&#x223c;0.01&#xa0;&#xb5;m<sup>2</sup>) showing a four-fold increase in antibacterial activity relative to larger sheets (&#x223c;0.65&#xa0;&#xb5;m<sup>2</sup>) in coatings (<xref ref-type="bibr" rid="B185">Perreault et al., 2015</xref>). The shape is equally decisive: sharp, high-aspect-ratio edges such as those in GO nanowalls or CNT tips mechanically disrupt bacterial membranes, significantly reducing survival rates of <italic>E. coli</italic> and <italic>S. aureus</italic> (<xref ref-type="bibr" rid="B160">Mohammed et al., 2020</xref>). Surface functionalization further modulates activity: oxygenated groups (&#x2013;COOH, &#x2013;OH), reduced forms (rGO), or conjugation with Cu<sup>2&#x2b;</sup> or Ag nanoparticles enhance dispersion, surface charge, ROS production, and targeted adhesion, with rGO&#x2013;Cu hybrids achieving two orders of magnitude greater antibacterial effect compared to rGO alone (<xref ref-type="bibr" rid="B243">Tu et al., 2021</xref>). Thus, tuning CNM size, tailoring sharp morphologies, and engineering surface chemistries&#x2014;especially <italic>via</italic> metal decoration or functional groups&#x2014;synergistically optimize antimicrobial performance (<xref ref-type="bibr" rid="B45">Cobos et al., 2020</xref>; <xref ref-type="bibr" rid="B120">Khairol Anuar et al., 2021</xref>). Although CNMs hold promise for modulating gut microbial activity and enhancing certain health-related functions, their long-term impact on microbial diversity and gut health remains uncertain. Prolonged or high-level exposure may disrupt normal microbial communities and even promote the development of antibiotic resistance (<xref ref-type="fig" rid="F2">Figure 2</xref>) (<xref ref-type="bibr" rid="B269">Xie et al., 2016</xref>). Therefore, while the therapeutic potential of CNMs is notable, careful evaluation of their safety and biological interactions is essential.</p>
<p>The interactions of ENMs with the human microbiome cannot be fully understood without considering their broader ecological footprint. ENMs released into soil, water, and air do not remain confined to the environment but can re-enter the food chain and drinking water, ultimately influencing human exposure. For instance, agricultural ENMs that alter soil or rhizosphere microbial communities may indirectly affect nutritional and microbial inputs to the human gut <italic>via</italic> crops (<xref ref-type="bibr" rid="B159">Mgadi et al., 2024</xref>; <xref ref-type="bibr" rid="B64">Dixit et al., 2024</xref>); similarly, ENM contamination of aquatic systems can influence water-borne microbiota that serve as reservoirs of antimicrobial resistance genes (<xref ref-type="bibr" rid="B48">Cui and Smith, 2022</xref>). Studies show that exposure to polluted or microbe-rich environments correlates with shifts in gut microbiome composition and diversity, suggesting a soil-plant-gut axis of microbial transmission and those environmental pollutants select for microbiome functionality in the gut (<xref ref-type="bibr" rid="B147">Ma et al., 2025</xref>; <xref ref-type="bibr" rid="B54">De Filippis et al., 2024</xref>). Thus, environmental and human microbiomes are interconnected through shared exposure pathways, bioaccumulation, and resistome exchange, highlighting the need to view ENM&#x2013;microbiome interactions not as isolated domains but as part of a continuum linking ecosystem health and human health.</p>
</sec>
</sec>
<sec id="s4">
<label>4</label>
<title>ENMs and environmental microbial communities</title>
<p>ENMs, such as nano-TiO<sub>2</sub> and various metal NPs, have a profound impact on water-borne microbial communities, influencing key ecological functions like nutrient cycling and overall ecosystem health (<xref ref-type="table" rid="T2">Table 2</xref>). Chronic exposure to ENMs can disrupt the structure and function of microbial communities, leading to significant changes in biogeochemical processes essential for ecosystem sustainability. For instance, long-term exposure to nano-TiO<sub>2</sub> has been found to reduce biofilm biomass and alter microbial community composition by decreasing the presence of taxa involved in nitrogen fixation and denitrification, the processes critical to nutrient cycling (<xref ref-type="bibr" rid="B23">Binh et al., 2016</xref>; <xref ref-type="bibr" rid="B179">Passarelli et al., 2020</xref>). Similarly, metal NPs such as silver and copper exhibit toxicity toward microbial populations, impairing enzymatic activities necessary for processes like nitrogen fixation and organic matter decomposition (<xref ref-type="bibr" rid="B186">Peyrot et al., 2014</xref>; <xref ref-type="bibr" rid="B42">Chhipa, 2021</xref>). ENMs also affect microbial activity by suppressing fundamental metabolic processes including respiration and photosynthesis, which are essential for maintaining ecosystem functions (<xref ref-type="bibr" rid="B23">Binh et al., 2016</xref>). Additionally, the presence of ENMs can lead to a shift in microbial community composition, favoring resistant taxa while reducing those crucial for nutrient cycling, thereby impairing key ecosystem services (<xref ref-type="bibr" rid="B23">Binh et al., 2016</xref>). These disruptions can have cascading effects on ecosystem health, such as reduced soil fertility and compromised ecosystem functionality, ultimately threatening agricultural productivity and environmental stability (<xref ref-type="bibr" rid="B275">Yadav and Yadav, 2024</xref>). Despite these concerns, some studies suggest that under certain conditions, ENMs may also enhance specific microbial functions or increase microbial resilience, highlighting a complex and context-dependent interaction between ENMs and microbial communities. As such, a comprehensive understanding of the dual roles of ENMs, both beneficial and detrimental is essential for evaluating their environmental impact and guiding their responsible use (<xref ref-type="bibr" rid="B275">Yadav and Yadav, 2024</xref>).</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Effects of Engineered Nanomaterials (ENMs) on environmental microbiota.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Nanomaterial</th>
<th align="left">System studied</th>
<th align="left">Effects on microbiota</th>
<th align="left">Mechanisms of action</th>
<th align="left">Ecological implications</th>
<th align="left">Key references</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">TiO<sub>2</sub> NPs</td>
<td align="left">Aquatic ecosystems</td>
<td align="left">Diminish nitrogen-fixing bacteria like <italic>Azotobacter</italic> and denitrifiers such as <italic>Pseudomonas</italic>, biofilm loss, altered community composition</td>
<td align="left">Inducing reactive oxygen species (ROS) generation, inhibition of respiration or photosynthesis</td>
<td align="left">Reduced nutrient cycling, risk of algal blooms</td>
<td align="left">
<xref ref-type="bibr" rid="B22">Binh et al. (2014)</xref>
</td>
</tr>
<tr>
<td align="left">CuO NPs</td>
<td align="left">Aquatic ecosystems</td>
<td align="left">Disruption of critical microbial functions&#x2014;such as nitrate reduction; enzyme inhibition</td>
<td align="left">Membrane damage, enzyme suppression</td>
<td align="left">Reduced denitrification efficiency</td>
<td align="left">
<xref ref-type="bibr" rid="B230">Su et al. (2015)</xref>
</td>
</tr>
<tr>
<td align="left">AgNPs, ZnO NPs</td>
<td align="left">Soil microbiomes</td>
<td align="left">Lowering diversity indices (shannon, simpson); inhibited dehydrogenase, urease, phosphatase</td>
<td align="left">Dose-dependent enzymatic inhibition</td>
<td align="left">Reduced soil fertility and nutrient cycling</td>
<td align="left">
<xref ref-type="bibr" rid="B9">Asadishad et al. (2018)</xref>
</td>
</tr>
<tr>
<td align="left">ENMs (Ag, ZnO, Cu, CeO<sub>2</sub>, CNMs)</td>
<td align="left">Plant&#x2013;microbe interactions</td>
<td align="left">Suppress mycorrhizal fungi and nitrogen-fixers; sometimes enhance plant growth</td>
<td align="left">Antimicrobial activity, altered signaling</td>
<td align="left">Reduced nodulation, impaired symbiosis; but potential as smart fertilizers</td>
<td align="left">
<xref ref-type="bibr" rid="B164">Mortimer et al. (2020)</xref>
</td>
</tr>
<tr>
<td align="left">ZnO, Ag, CuNPs</td>
<td align="left">Resistance traits</td>
<td align="left">Increased horizontal gene transfer (HGT) &#x26; antibiotic resistance gene (ARG) transfer; plasmid conjugation</td>
<td align="left">ROS, enhanced membrane permeability, SOS response</td>
<td align="left">Spread of antimicrobial resistance</td>
<td align="left">
<xref ref-type="bibr" rid="B152">Markowicz et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">TiO<sub>2</sub> NPs</td>
<td align="left">Soil microbiomes and aquatic ecosystems</td>
<td align="left">Changes in microbial community composition in soil and water; toxicity to aquatic organisms (e.g., reduced survival, growth inhibition in zebrafish and daphnia); disruption of photosynthesis and growth in plants and algae</td>
<td align="left">Altered nutrient cycling via impact on microbial communities; bioaccumulation in aquatic food webs; photocatalytic activity under UV resulting in ROS generation causing oxidative stress in aquatic or soil organisms; physical adsorption onto cell surfaces altering permeability</td>
<td align="left">Toxicity to aquatic organisms (zebrafish); developmental effects in nematodes; growth and stress responses in plants</td>
<td align="left">
<xref ref-type="bibr" rid="B299">Wang S. et al. (2022)</xref>; <xref ref-type="bibr" rid="B300">Yamini et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">ZnO NPs</td>
<td align="left">Soil microbiomes</td>
<td align="left">Toxic effects on soil microbes, altering nitrogen fixation and organic matter cycling</td>
<td align="left">Dissolution to Zn<sup>2&#x2b;</sup> ions causes metal ion toxicity; ROS production leading to oxidative stress and DNA/protein damage; disruption of enzymatic and metabolic pathways in microbes, algae, and plants; particle aggregation influencing bioavailability and sedimentation in aquatic systems</td>
<td align="left">Disruption of reproduction and growth in aquatic species; developmental and stress effects in plants and nematodes</td>
<td align="left">
<xref ref-type="bibr" rid="B299">Wang S. et al. (2022)</xref>; <xref ref-type="bibr" rid="B300">Yamini et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">AgNPs</td>
<td align="left">Soil</td>
<td align="left">Reduced microbial diversity; inhibition of nitrifying or denitrifying bacteria (<italic>Nitrosomonas</italic>, <italic>Pseudomonas</italic>); altered community composition</td>
<td align="left">Release of Ag<sup>&#x2b;</sup> ions results in enzyme inhibition; ROS generation; disruption of nitrogen cycle</td>
<td align="left">Reduced N cycling, soil fertility loss, risk of resistant microbes</td>
<td align="left">
<xref ref-type="bibr" rid="B44">Choi and Hu (2009)</xref>
</td>
</tr>
<tr>
<td align="left">ZnO NPs</td>
<td align="left">Soil microbiomes</td>
<td align="left">Abundance of beneficial microbes (<italic>Rhizobium</italic>, <italic>Bacillus</italic>); reduced microbial richness at higher concentration</td>
<td align="left">Dissolution to Zn<sup>2&#x2b;</sup> ions; ROS-mediated damage</td>
<td align="left">Impaired plant-microbe interactions; reduced soil health</td>
<td align="left">
<xref ref-type="bibr" rid="B84">Ge et al. (2012)</xref>
</td>
</tr>
<tr>
<td align="left">TiO<sub>2</sub> NPs</td>
<td align="left">Soil microbiomes</td>
<td align="left">Depression in microbial richness and fungal/bacterial ratio shifts</td>
<td align="left">Photocatalytic ROS under UV; adsorption onto microbial surfaces</td>
<td align="left">Potential disruption of C and N cycling; context-dependent effects</td>
<td align="left">
<xref ref-type="bibr" rid="B223">Simonin and Richaume (2015)</xref>
</td>
</tr>
<tr>
<td align="left">CNTs</td>
<td align="left">Soil microbiomes</td>
<td align="left">Dose-dependent microbial inhibition; upregulating Actinobacteria, degrading proteobacteria</td>
<td align="left">Physical piercing of membranes; ROS production; altered soil pH or micro-niches</td>
<td align="left">Altered microbial balance leading to long-term shifts in nutrient cycling</td>
<td align="left">
<xref ref-type="bibr" rid="B115">Kang et al. (2008)</xref>; <xref ref-type="bibr" rid="B206">Rodrigues et al. (2013)</xref>
</td>
</tr>
<tr>
<td align="left">Graphene oxide</td>
<td align="left">Soil microbiomes</td>
<td align="left">Degrading the abundance of proteobacteria and firmicutes; disruption of soil enzyme activity</td>
<td align="left">Strong adsorption to microbial cell walls; oxidative stress</td>
<td align="left">Disturbance of enzymatic soil processes; long-term microbial shifts</td>
<td align="left">
<xref ref-type="bibr" rid="B271">Xiong et al. (2018)</xref>
</td>
</tr>
<tr>
<td align="left">Iron oxide nanoparticles (Fe<sub>3</sub>O<sub>4</sub>, Fe<sub>2</sub>O<sub>3</sub>)</td>
<td align="left">Soil microbiomes</td>
<td align="left">Low levels (1 and 10&#xa0;mg/kg soil) stimulated microbial metabolic activity whereas higher concentrations (50&#x2013;500&#xa0;mg/kg) had variable or inhibitory effects</td>
<td align="left">Released iron ion causes redox imbalance; enzyme interference</td>
<td align="left">Potential stimulation of nutrient cycling at low doses; inhibition at high doses</td>
<td align="left">
<xref ref-type="bibr" rid="B208">Rui et al. (2016)</xref>
</td>
</tr>
<tr>
<td align="left">Aluminum oxide nanoparticles (Al<sub>2</sub>O<sub>3</sub> NPs)</td>
<td align="left">Soil microbiomes</td>
<td align="left">Altered bacterial community composition; reduced fungal growth</td>
<td align="left">Al<sup>3&#x2b;</sup> ion release; physical interaction with microbial membranes</td>
<td align="left">Shifts in soil microbial balance; potential inhibition of plant-microbe symbiosis</td>
<td align="left">
<xref ref-type="bibr" rid="B73">Fajardo et al. (2014)</xref>; <xref ref-type="bibr" rid="B8">Ansari et al. (2014)</xref>; <xref ref-type="bibr" rid="B210">Sadiq et al. (2009)</xref>
</td>
</tr>
<tr>
<td align="left">AgNPs</td>
<td align="left">Aquatic ecosystems</td>
<td align="left">Reduced biofilm biomass; degrading nitrifying bacteria (<italic>Nitrosomonas</italic>); altered community composition; inhibition of denitrifiers (<italic>Pseudomonas</italic>)</td>
<td align="left">Ag<sup>&#x2b;</sup> ion release; ROS generation; enzyme inhibition (nitrification, denitrification)</td>
<td align="left">Disruption of nitrogen cycling; reduced water quality; microbial dysbiosis</td>
<td align="left">
<xref ref-type="bibr" rid="B51">Das et al. (2012)</xref>
</td>
</tr>
<tr>
<td align="left">ZnO NPs</td>
<td align="left">Aquatic ecosystems</td>
<td align="left">Reduced bacterial abundance and diversity; shifts toward Zn-resistant taxa; altered algal&#x2013;bacterial interactions</td>
<td align="left">Zn<sup>2&#x2b;</sup> ion release; ROS-mediated toxicity</td>
<td align="left">Impaired primary productivity; disruption of nutrient cycling; risk of resistance</td>
<td align="left">
<xref ref-type="bibr" rid="B264">Wu and Duncan (2020)</xref>
</td>
</tr>
<tr>
<td align="left">TiO<sub>2</sub> NPs</td>
<td align="left">Aquatic ecosystems</td>
<td align="left">Degraded biofilm biomass; altered microbial composition; reduced abundance of nitrogen-fixing bacteria (<italic>Azotobacter</italic>)</td>
<td align="left">Photocatalytic ROS under UV; cell membrane damage</td>
<td align="left">Impaired nutrient cycling; reduced ecosystem stability in freshwater</td>
<td align="left">
<xref ref-type="bibr" rid="B41">Cherchi and Gu (2010)</xref>
</td>
</tr>
<tr>
<td align="left">Graphene oxide</td>
<td align="left">Aquatic ecosystems</td>
<td align="left">Degradedbacterial richness; inhibition of cyanobacteria and green algae; shifts in aquatic microbial assemblages</td>
<td align="left">Strong adsorption to cell walls; oxidative stress</td>
<td align="left">Reduced algal&#x2013;bacterial symbiosis; altered oxygen production</td>
<td align="left">
<xref ref-type="bibr" rid="B137">Li et al. (2020)</xref>; <xref ref-type="bibr" rid="B72">Evariste et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">CuO NPs</td>
<td align="left">Aquatic ecosystems</td>
<td align="left">Reducedmicrobial biomass; inhibition of nitrification and denitrification pathways; altered bacterial community</td>
<td align="left">Cu<sup>2&#x2b;</sup> ion release; oxidative stress; enzyme inhibition</td>
<td align="left">Reduced nitrogen removal capacity; eutrophication risk</td>
<td align="left">
<xref ref-type="bibr" rid="B221">Sielska and Skuza (2025)</xref>; <xref ref-type="bibr" rid="B261">Wang Z. et al. (2024)</xref>
</td>
</tr>
<tr>
<td align="left">Iron oxide nanoparticles (Fe<sub>3</sub>O<sub>4</sub>, Fe<sub>2</sub>O<sub>3</sub>)</td>
<td align="left">Aquatic ecosystems</td>
<td align="left">Stimulation of some microbial groups at low levels whereas inhibition of diversity at higher concentrations</td>
<td align="left">Iron ion release affecting redox balance; interference with microbial enzymes</td>
<td align="left">Possible enhancement of nutrient cycling at low doses; inhibition at high doses</td>
<td align="left">
<xref ref-type="bibr" rid="B78">Gabrielyan et al. (2019)</xref>; <xref ref-type="bibr" rid="B30">Caixeta et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Cerium oxide nanoparticles (CeO<sub>2</sub> NPs)</td>
<td align="left">Aquatic ecosystems</td>
<td align="left">Altered aquatic microbial community composition; inhibition of biofilm formation at high concentration</td>
<td align="left">ROS scavenging at low doses; ROS induction at high doses</td>
<td align="left">Potential dual role with antioxidant protection and microbial toxicity</td>
<td align="left">
<xref ref-type="bibr" rid="B101">Hoecke et al. (2009)</xref>; <xref ref-type="bibr" rid="B83">Garc&#xed;a et al. (2012)</xref>
</td>
</tr>
</tbody>
</table>
</table-wrap>
<sec id="s4-1">
<label>4.1</label>
<title>Impact of ENMs on aquatic ecosystems</title>
<p>ENMs, such as nano-TiO<sub>2</sub> and various metal NPs, profoundly affect aquatic microbial communities, disrupting ecological processes like nutrient cycling and ecosystem stability (<xref ref-type="table" rid="T2">Table 2</xref>) (<xref ref-type="fig" rid="F2">Figure 2</xref>). In freshwater systems, chronic exposure to nano-TiO<sub>2</sub> can drastically reduce biofilm biomass and alter community composition, particularly diminishing nitrogen-fixing bacteria like <italic>Azotobacter</italic> and denitrifiers such as <italic>Pseudomonas</italic>, which play essential roles in nitrogen cycling (<xref ref-type="bibr" rid="B22">Binh et al., 2014</xref>). Short-term exposure further highlights species-specific effects: nano-TiO<sub>2</sub> has been shown to depress <italic>Bacillus subtilis</italic> and <italic>Aeromonas hydrophila</italic>, while paradoxically enhancing growth of <italic>Arthrobacter</italic> and <italic>Klebsiella</italic>, likely by photo-oxidizing organic matter into more bioavailable forms (<xref ref-type="bibr" rid="B22">Binh et al., 2014</xref>). Simultaneously, metal NPs like copper oxide (CuO NPs) disrupt critical microbial function such as nitrate reduction by damaging cell membranes, down-regulating enzymes like NADH dehydrogenase, cytochromes, nitrate and nitrite reductases in model denitrifier <italic>Paracoccus denitrificans</italic>, ultimately reducing denitrification efficiency by roughly 36% (from &#x223c;98% to &#x223c;62%) at concentrations between 0.05&#x2013;0.25&#xa0;mg/L (<xref ref-type="bibr" rid="B230">Su et al., 2015</xref>).</p>
<p>ENMs also impair microbial metabolic pathways integral to ecosystem function. Nano-TiO<sub>2</sub> and ZnO NPs suppress respiration and photosynthesis in primary producers; for instance, ZnO exposure lowers photosynthetic activity in cyanobacteria like <italic>Microcystis aeruginosa</italic>. Nano-TiO<sub>2</sub> inhibits metabolic activity in algae and bacteria, reshaping taxa distribution by reducing sensitive algal species and allowing more resistant cyanobacteria to thrive, raising concerns around harmful algal blooms (<xref ref-type="bibr" rid="B38">Chen B. et al., 2022</xref>). These disruptions carry serious ecological consequences (<xref ref-type="fig" rid="F2">Figure 2</xref>). In agricultural runoff zones, ENMs can reduce microbial diversity and soil nutrient availability, decreasing fertility and crop yield. In wetlands, altered biofilm and microbial enzyme activity impairs organic matter decomposition, affecting carbon sequestration and water purification. However, not all effects are negative: low concentrations of iron oxide NPs have been observed to stimulate growth and denitrification in <italic>P. denitrificans</italic> and other denitrifiers, illustrating the nuanced, context-dependent nature of ENM&#x2013;microbe interactions. Therefore, ENMs exert complex dual roles in aquatic ecosystems: they can both disrupt and potentially enhance microbial community structure and function. A deeper, context-sensitive understanding of these interactions is essential to assess environmental risks and guide responsible applications of nanotechnology.</p>
<p>The influence of ENMs on bioaccumulation and ecotoxicological effects within keystone microbial species is profound and multifaceted. Silver and copper NPs, for instance, readily accumulate in microbial cells, disrupting physiological functions and reshaping community structures based on concentration and particle type (<xref ref-type="bibr" rid="B96">He et al., 2014</xref>; <xref ref-type="bibr" rid="B254">Von Moos and Slaveykova, 2014</xref>). In freshwater sediments, exposure to citrate- and PVP-coated AgNPs at 0, 25, 50, 75, 100, and 125&#xa0;mg/L caused dose-dependent inhibition of microbial functional diversity. At the highest concentration (125&#xa0;mg/L), citrate-AgNP significantly reduced microbial catabolic activity by up to 80% and diminished both substrate richness and diversity, impairing organic matter degradation and broader nutrient cycling (<xref ref-type="bibr" rid="B130">Kusi et al., 2020</xref>). This bioaccumulation at lower trophic levels also poses a risk of trophic transfer, potentially leading to biomagnification in higher organisms.</p>
<p>Ecotoxicologically, ENMs can both generate ROS at their surfaces (e.g., <italic>via</italic> catalytic activity or metal ion release) and induce ROS production within organisms (e.g., <italic>via</italic> mitochondrial dysfunction or activation of NADPH oxidases) (<xref ref-type="bibr" rid="B156">Mendoza and Brown, 2019</xref>; <xref ref-type="bibr" rid="B85">Ge et al., 2019</xref>). This oxidative stress disrupts essential enzymatic and metabolic functions such as nitrogen fixation, respiration, and organic matter decomposition, all critical for ecosystem sustainability (<xref ref-type="bibr" rid="B254">Von Moos and Slaveykova, 2014</xref>; <xref ref-type="bibr" rid="B286">Zhai et al., 2018</xref>; <xref ref-type="bibr" rid="B80">Gambardella and Pinsino, 2022</xref>). In microbial and algal models (e.g., <italic>Chlorella vulgaris</italic>), exposure to CNTs and metal-oxide NPs triggered elevated antioxidant enzyme activity (e.g., superoxide dismutase) alongside ROS-induced damage and reduced cell viability (<xref ref-type="bibr" rid="B182">Pereira et al., 2014</xref>). In environmental contexts, even low levels of AgNPs reduced metabolic diversity in organic-matter-associated microbial communities, which in turn indirectly stunted invertebrate growth in aquatic food webs (<xref ref-type="bibr" rid="B286">Zhai et al., 2018</xref>; <xref ref-type="bibr" rid="B91">Guo et al., 2019</xref>; <xref ref-type="bibr" rid="B15">Bao et al., 2016</xref>; <xref ref-type="bibr" rid="B130">Kusi et al., 2020</xref>). The toxicity of these materials is closely tied to their physicochemical characteristics such as size, shape, surface chemistry, ion dissolution rates, all of which modulate interactions with microbial cells (<xref ref-type="bibr" rid="B240">Triboulet et al., 2013</xref>; <xref ref-type="bibr" rid="B96">He et al., 2014</xref>; <xref ref-type="bibr" rid="B182">Pereira et al., 2014</xref>; <xref ref-type="bibr" rid="B254">Von Moos and Slaveykova, 2014</xref>; <xref ref-type="bibr" rid="B130">Kusi et al., 2020</xref>). For instance, the ecotoxicity of silver varies significantly between metallic AgNPs and their sulfide-transformed forms (Ag<sub>2</sub>S), with reduced bioavailability and toxicity in soils (<xref ref-type="bibr" rid="B47">Courtois et al., 2019</xref>). Copper NPs similarly trigger oxidative stress and metabolic shifts in bacteria, affecting glutathione levels and antioxidant enzyme pathways (<xref ref-type="fig" rid="F2">Figure 2</xref>) (<xref ref-type="bibr" rid="B197">Rana and Kalaichelvan, 2013</xref>; <xref ref-type="bibr" rid="B240">Triboulet et al., 2013</xref>; <xref ref-type="bibr" rid="B108">Javurek et al., 2017</xref>).</p>
<p>Despite these adverse outcomes, there is emerging potential for ENMs in bioremediation applications, where targeted use of certain NPs can enhance microbial degradation of pollutants. This highlights a complex dual role: while ENMs may pose significant ecological hazards, they also offer novel opportunities for environmental management. However, addressing this duality requires nuanced and context-aware research to assess long-term impacts and guide responsible use of nanotechnologies.</p>
</sec>
<sec id="s4-2">
<label>4.2</label>
<title>Impact of ENMs on soil microbiome</title>
<p>ENMs significantly influence soil microbial diversity and enzymatic activities, thereby affecting soil health and agricultural productivity (<xref ref-type="fig" rid="F2">Figure 2</xref>). Exposure to metal ENMs such as AgNPs, ZnO NPs and TiO<sub>2</sub> NPs can significantly alter microbial metabolic diversity and key enzyme functions in soils (<xref ref-type="table" rid="T2">Table 2</xref>) (<xref ref-type="bibr" rid="B196">Rajput et al., 2023</xref>; <xref ref-type="bibr" rid="B106">Islam, 2025</xref>). In one study, metal ENMs like AgNPs and ZnO NPs altered community-level physiological profiles of soil bacteria and significantly decreased the diversity indices, such as Shannon&#x2019;s diversity index, Evenness diversity index, and Simpson&#x2019;s diversity index while TiO<sub>2</sub> NPs had no detectable impact (<xref ref-type="bibr" rid="B9">Asadishad et al., 2018</xref>; <xref ref-type="bibr" rid="B34">Chavan and Nadanathangam, 2020</xref>; <xref ref-type="bibr" rid="B275">Yadav and Yadav, 2024</xref>). Further, soil amendments with AgNPs, ZnO NPs, and CuO NPs showed dose-dependent effects on enzymatic activity: ZnO and CuO either enhanced or had no effect at moderate doses (1&#x2013;10&#xa0;mg/kg), while AgNPs at higher concentrations (100&#xa0;mg/kg) inhibited enzymes such as dehydrogenase, phosphatase, and urease (<xref ref-type="bibr" rid="B241">Tripathi et al., 2023</xref>). High levels of ZnO, TiO<sub>2</sub>, and CeO<sub>2</sub> (around 1,000&#xa0;mg/kg) also reduced populations of <italic>Azotobacter</italic> and other nutrient-solubilizing bacteria, along with suppressed enzyme activities. AgNPs are reported to suppress populations of essential nitrogen-fixing and nitrifying microbes, including <italic>Rhizobium</italic> and <italic>Nitrosomonas</italic>, which disrupts nitrogen cycling processes in soil ecosystems (<xref ref-type="bibr" rid="B217">Shah and Belozerova, 2009</xref>). Likewise, ZnO NPs have been found to impair microbial respiration and inhibit key enzymatic activities, such as dehydrogenase and urease, both of which are vital for organic matter breakdown and nutrient recycling (<xref ref-type="bibr" rid="B178">Parada et al., 2019</xref>). In another study, acute exposure to CuO NPs (10&#x2013;500&#xa0;mg&#xa0;kg<sup>-1</sup>) through nano-pesticide markedly inhibited soil denitrification, with the highest dose (500&#xa0;mg&#xa0;kg<sup>-1</sup>) causing an 11-fold increase in nitrate accumulation and a 10.2%&#x2013;24.1% reduction in N<sub>2</sub>O emissions. This suppression was linked to decreased activities of nitrate reductase and nitric oxide reductase, along with inhibited electron transport system activity, altered expression of denitrifying functional genes, and shifts in bacterial community composition (<xref ref-type="bibr" rid="B293">Zhao et al., 2020</xref>). Similarly, only 90-day exposure of agricultural soils to TiO<sub>2</sub> NPs (1 and 500&#xa0;mg&#xa0;kg<sup>-1</sup>) significantly inhibited nitrification enzyme activities and reduced the abundance of ammonia-oxidizing microorganisms, as indicated by decreased <italic>amoA</italic> gene copies. This suppression cascaded to reduce denitrification enzyme activity, with declines in <italic>nirK</italic> and <italic>nirS</italic> gene abundances, alongside marked shifts in bacterial community structure, even at the lowest realistic NP concentration (<xref ref-type="bibr" rid="B224">Simonin et al., 2016</xref>). These disruptions can impair soil nutrient cycling. Specifically, enzymes critical for organic matter decomposition and nutrient release such as urease, phosphatase, and dehydrogenase show decreased activity upon ENM exposure, threatening soil fertility (<xref ref-type="fig" rid="F2">Figure 2</xref>) (<xref ref-type="bibr" rid="B9">Asadishad et al., 2018</xref>; <xref ref-type="bibr" rid="B33">Chavan and Nadanathangam, 2019</xref>). Moreover, ZnO and CuO NPs may reprogram microbial metabolic pathways by upregulating nitrogen fixation genes (nifH, amoA) while downregulating denitrification genes (norB, nosZ), leading to imbalances in nitrogen cycling (<xref ref-type="bibr" rid="B144">Luche et al., 2016</xref>; <xref ref-type="bibr" rid="B232">Sun et al., 2022</xref>; <xref ref-type="bibr" rid="B241">Tripathi et al., 2023</xref>). Despite these negative impacts, low to moderate ENM levels could stimulate microbial resilience. Biogenic NMs like nanozeolite and nanochitosan, combined with plant probiotics, were found to enhance dehydrogenase, alkaline phosphatase, and fluorescein diacetate hydrolase activities&#x2014;doubling or tripling enzyme performance under agricultural conditions (<xref ref-type="bibr" rid="B245">Upadhayay et al., 2023</xref>), a promising application in sustainable agriculture.</p>
<p>ENMs profoundly affect plant&#x2013;microbe interactions, especially those involving mycorrhizal fungi and nitrogen-fixing bacteria, with outcomes that vary depending on material type, concentration, and microbial partners (<xref ref-type="table" rid="T2">Table 2</xref>). Arbuscular mycorrhizal fungi, essential for enhancing plant nutrient uptake, can be adversely impacted by ENMs, which inhibit fungal growth and disrupt nutrient exchange between plants and soil (<xref ref-type="bibr" rid="B283">Yu M. et al., 2020</xref>; <xref ref-type="bibr" rid="B252">Vera-Reyes et al., 2023</xref>). Additionally, nitrogen-fixing bacteria such as <italic>Bradyrhizobium diazoefficiens</italic> are sensitive to ENM exposure: cerium oxide nanoparticles (CeO<sub>2</sub> NPs) and multi-walled carbon nanotubes (MWCNTs) can suppress their growth, reduce nodulation competitiveness, and interfere with plant&#x2013;bacteria signaling critical for effective symbiosis (<xref ref-type="bibr" rid="B164">Mortimer et al., 2020</xref>). ENMs further reshape the soil microbiome, altering processes such as mineralization and nitrogen fixation (<xref ref-type="fig" rid="F2">Figure 2</xref>). Their antimicrobial properties can decrease beneficial microbial populations, further disrupting plant&#x2013;microbe symbioses. This disruption undermines soil functions that are key to plant health. However, context matters: in certain situations, NMs have been shown to enhance plant growth and mitigate abiotic stress by supporting beneficial microbial interactions and functioning as &#x201c;smart fertilizers&#x201d; (<xref ref-type="bibr" rid="B146">Ma et al., 2022</xref>; <xref ref-type="bibr" rid="B18">Berrios et al., 2023</xref>; <xref ref-type="bibr" rid="B226">Sodhi et al., 2025</xref>). At low concentrations (&#x223c;5&#xa0;mg/kg Ag and 50&#xa0;mg/kg Zn and Ti), ENMs in biosolids did not adversely affect <italic>Medicago truncatula</italic> growth or metal accumulation in shoots. Instead, they enhanced symbiotic interactions with rhizobia (<italic>Sinorhizobium meliloti</italic>), as reflected by a higher nodule number, and significantly increased total soil microbial biomass. Furthermore, ENM exposure at low concentrations altered microbial community composition, increasing Gram-negative and anaerobic bacteria while reducing eukaryotic abundance. These findings suggest potential stimulatory effects of transformed ENMs on soil microbial activity and plant&#x2013;rhizobia symbiosis (<xref ref-type="bibr" rid="B35">Chen et al., 2017</xref>). Exposure to ZnO NPs as nanofertilizer at 10&#xa0;mg/kg and 100&#xa0;mg/kg significantly reshaped the rhizospheric bacterial community structure, particularly altering the abundance of Cyanobacteria and key plant growth-promoting taxa, while alpha diversity remained stable. These compositional shifts were more pronounced at the higher dose (100&#xa0;mg/kg), suggesting dose-dependent effects of ZnO NPs on soil microbial ecology. While 10&#xa0;mg/kg ZnO NPs also coincided with enhanced lettuce biomass and photosynthetic rate, no additional plant growth benefits were observed at 100&#xa0;mg/kg, despite the intensified microbial community changes (<xref ref-type="bibr" rid="B272">Xu et al., 2018</xref>). Therefore, the effects of ENMs on soil microbial communities are complex. High concentrations of metal-based NPs tend to inhibit diversity and enzyme function compromising nutrient cycling and soil fertility, while the use of certain nanobiofertilizers at controlled doses shows potential for improving microbial function and crop productivity (<xref ref-type="bibr" rid="B291">Zhang et al., 2024</xref>). Therefore, ENMs offer potential agricultural benefits such as improved nutrient delivery and stress resistance, while their adverse effects on crucial microbial partnerships raise concerns about their long-term ecological impact. This underscores the need for targeted research to balance ENM applications benefits against ecological risks.</p>
</sec>
</sec>
<sec id="s5">
<label>5</label>
<title>Cross-talk between ENMs and microbial resistance</title>
<p>ENMs are increasingly implicated in exacerbating antimicrobial resistance among microbial communities by facilitating the persistence and dissemination of antimicrobial resistance genes (ARGs). Notably, metal oxide NPs such as ZnO NPs have been shown to promote horizontal gene transfer among bacteria. In laboratory and soil studies, ZnO NPs increased transformation frequency in <italic>E. coli</italic> by approximately 1.8-fold and enhanced the copy number of metal resistance&#x2013;linked genes, indicating co-selection of resistance mechanisms (<xref ref-type="bibr" rid="B152">Markowicz et al., 2023</xref>; <xref ref-type="bibr" rid="B176">Otinov et al., 2020</xref>; <xref ref-type="bibr" rid="B260">Wang X. et al., 2024</xref>; <xref ref-type="bibr" rid="B4">Alav and Buckner, 2024</xref>). Furthermore, AgNPs and CuNPs stimulate the conjugative transfer of ARG-laden plasmids across bacterial genera; for instance, silver ions and AgNPs have been shown to facilitate plasmid-mediated resistance gene transfer, and CuNPs promoted multi-antibiotic resistance gene spread in environmental bacteria (<xref ref-type="bibr" rid="B282">Yu K. et al., 2020</xref>). The mechanisms underlying these effects include enhanced horizontal gene transfer among bacterial communities, particularly fostering the spread of ARGs through oxidative stress, increased membrane permeability, induction of the bacterial SOS response, and upregulation of conjugation-related genes (<xref ref-type="fig" rid="F2">Figure 2</xref>) (<xref ref-type="bibr" rid="B282">Yu K. et al., 2020</xref>). Sub-lethal exposure to ENMs like nano-alumina (Al<sub>2</sub>O<sub>3</sub>) has been shown to induce ROS, which damage cell membranes and create pores that facilitate plasmid uptake; this also triggers the SOS DNA damage response that further promotes plasmid transformation and conjugation (e.g., <italic>pBR322</italic> into <italic>E. coli</italic> and <italic>S. aureus</italic>)&#x2014;a striking increase in horizontal gene transfer efficiency linked directly to NP presence (<xref ref-type="bibr" rid="B63">Ding et al., 2016</xref>). Similarly, nanofullerene (nC<sub>60</sub>) exposure increases ROS generation and membrane disruption, upregulating genes crucial for DNA transfer and conjugative machinery (e.g., <italic>trbBp</italic>, <italic>korA/B</italic>) in exposed bacteria (<xref ref-type="bibr" rid="B110">Ji et al., 2020</xref>; <xref ref-type="bibr" rid="B7">Amaro et al., 2021</xref>). ENMs also act as environmental ARG reservoirs. For example, certain NPs can adsorb plasmids or ARG-containing DNA, protecting them from degradation and increasing their environmental persistence. CeO<sub>2</sub> NPs, in particular, have been investigated both for their facilitation and inhibition of antimicrobial resistance genes propagation; while some studies identified increased conjugation, others found that CeO<sub>2</sub> can suppress antimicrobial resistance genes transfer by reducing ROS and downregulating horizontal gene transferring genes (<xref ref-type="bibr" rid="B282">Yu K. et al., 2020</xref>; <xref ref-type="bibr" rid="B218">Sharma et al., 2025</xref>). Additionally, ENMs impose selective pressure on microbial communities: resistant strains, better able to cope with metal-induced stress, proliferate while susceptible strains decline leading to enrichment of antimicrobial resistance traits (<xref ref-type="bibr" rid="B171">Neethu et al., 2022</xref>).</p>
<p>Comprehensive reviews reinforce the notion that ENMs in environments from various sources such as wastewater treatment plants exert selective pressure on microbial communities and enhance horizontal gene transfer by increasing membrane permeability through both direct interaction and ROS-mediated damage, concurrently inducing genetic changes linked to conjugation (<xref ref-type="fig" rid="F2">Figure 2</xref>) (<xref ref-type="bibr" rid="B48">Cui and Smith, 2022</xref>; <xref ref-type="bibr" rid="B139">Li et al., 2025</xref>). Additionally, ENMs contribute to these effects by adsorbing extracellular ARGs and plasmids, protecting them from degradation and facilitating persistence and uptake in microbial populations (<xref ref-type="bibr" rid="B63">Ding et al., 2016</xref>; <xref ref-type="bibr" rid="B48">Cui and Smith, 2022</xref>; <xref ref-type="bibr" rid="B273">Xu et al., 2023</xref>; <xref ref-type="bibr" rid="B114">Kalli et al., 2023</xref>; <xref ref-type="bibr" rid="B116">Kaushik et al., 2023</xref>; <xref ref-type="bibr" rid="B166">Mosaka et al., 2023</xref>; <xref ref-type="bibr" rid="B139">Li et al., 2025</xref>). These processes lead to accelerated spread of resistance genes in microbial communities, with ENMs acting as vectors and catalysts for antimicrobial resistant gene propagation in wastewater and natural environments, a trend confirmed by increased antimicrobial resistant gene and mobile genetic element abundance following NP exposure (<xref ref-type="bibr" rid="B63">Ding et al., 2016</xref>; <xref ref-type="bibr" rid="B48">Cui and Smith, 2022</xref>; <xref ref-type="bibr" rid="B139">Li et al., 2025</xref>). However, research also suggests a potential dual role: emerging NP designs with antioxidant or electrochemical properties may attenuate ARG transmission, indicating a path toward mitigating antimicrobial resistance spread <italic>via</italic> ENMs. The ENMs may also hold beneficial potential in antimicrobial resistance mitigation by their use in targeted drug-delivery systems for antibiotics and/or having synergistic effects reducing the overall required dosage, lowering selective pressure and slowing resistance development (<xref ref-type="bibr" rid="B203">Ribeiro et al., 2022</xref>; <xref ref-type="bibr" rid="B5">AlQurashi et al., 2025</xref>; <xref ref-type="bibr" rid="B218">Sharma et al., 2025</xref>). For instance, encapsulation of enrofloxacin in PLGA and lignin NPs mitigated its disruptive effects on the gut microbiome compared to free enrofloxacin, with lignin-encapsulated Enro showing minimal impact on microbial diversity. Notably, NP delivery delayed the rise in ARG expression between 24 and 72&#xa0;h, suggesting a potential to reduce antibiotic-induced resistome shifts in the gut (<xref ref-type="bibr" rid="B97">Herrera et al., 2024</xref>). Nano-ZnO exposures have been reported to cause dose-dependent alterations in gut microbiota composition and diversity, suppressed SCFA production, and shifted key microbial functional pathways. While medium doses (2.5&#xa0;mg/L) reduced several ARGs by inhibiting host bacteria, low doses (0.1&#xa0;mg/L) unexpectedly enriched tetracycline resistance genes, highlighting potential risks to gut health and resistome stability (<xref ref-type="bibr" rid="B289">Zhang et al., 2021</xref>). Another study reported that during cultivation of leachate microbiota, ARG diversity and abundance dropped significantly (1.4&#x2013;3.2 log), with NPs&#x2014;especially metal oxides (CuO, ZnO)&#x2014;enhancing this attenuation in an ARG-specific manner. The attenuation was driven by metal-induced bacterial growth inhibition, dissolved ion stress, and internalized NPs inducing oxidative stress (ROS), which together reduced horizontal ARG transfer and damaged resistance genes (<xref ref-type="bibr" rid="B231">Su et al., 2019</xref>). Altogether, ENMs may promote antimicrobial resistance&#x2014;yet, with mindful design, they may also serve as tools to counteract microbial resistance dissemination in environmental as well as <italic>in vivo</italic> settings.</p>
<p>Another crucial aspect is ENMs in combination with existing pollutants, such as heavy metals, can synergistically drive microbial resistance, posing a complex environmental hazard (<xref ref-type="bibr" rid="B12">Balta et al., 2025</xref>). ENMs like TiO<sub>2</sub> NPs and ZnO NPs interact with heavy metals to alter their bioavailability, which may enhance metal uptake by microbes and foster resistance <italic>via</italic> genetic mutations or horizontal gene transfer. This synergy not only increases toxicity to microbial populations but also pressures communities to develop resistance mechanisms such as efflux pumps and biofilm formation (<xref ref-type="bibr" rid="B59">Dickinson et al., 2019</xref>; <xref ref-type="bibr" rid="B265">Wu et al., 2021</xref>). The combined presence of ENMs and pollutants alters microbial community structures, often favoring resistant strains over susceptible ones and intensifying resistance traits through continuous stress. Moreover, co-contamination with ENMs and organic pollutants can result in synergistic toxicity effects that are typically underestimated in conventional environmental risk assessments (<xref ref-type="bibr" rid="B244">Tufail et al., 2022</xref>; <xref ref-type="bibr" rid="B297">Zhu et al., 2024</xref>; <xref ref-type="bibr" rid="B172">Olawade et al., 2024</xref>). This increases the overall health risks posed by resistant pathogens by creating niches that sustain and spread antimicrobial resistance (<xref ref-type="bibr" rid="B12">Balta et al., 2025</xref>). Despite these challenges, the interaction between ENMs and pollutants also presents opportunities for novel antimicrobial strategies. By understanding these synergistic effects, researchers hope to develop targeted nanoparticle-based interventions that can disrupt resistant microbial communities or enhance contaminant removal, offering a balanced approach to combating antimicrobial resistance.</p>
</sec>
<sec id="s6">
<label>6</label>
<title>Tools and techniques for assessing ENM-Microbiome interactions</title>
<p>Assessing the impact of ENMs on microbiome interactions requires a comprehensive, multi-tiered approach that integrates high-throughput sequencing (16S rRNA, metagenomics, metatranscriptomics), functional assays (enzyme activity, SCFA profiling, metaproteomics, metabolomics), resistome analysis (qPCR, metagenomics), microscopy techniques (TEM, confocal), and <italic>in vitro</italic>/<italic>in vivo</italic> models (organoids and organ-on-a-chip technologies, gnotobiotic mice, &#x201c;Humanized&#x201d; murine models) to evaluate compositional, functional, and genetic changes. Advanced tools like meta-analyses and machine learning further enhance the interpretation of complex omics data and support a holistic understanding of ENM&#x2013;microbiome dynamics (<xref ref-type="bibr" rid="B79">Galloway-Pe&#xf1;a and Hanson, 2020</xref>; <xref ref-type="bibr" rid="B163">Moreno-Indias et al., 2021</xref>; <xref ref-type="bibr" rid="B165">Mortimer et al., 2021</xref>). A global meta-analysis involving over 2,100 observations demonstrated clear negative effects of ENMs on soil microbial diversity, biomass, and functional enzyme activity, with machine learning models effectively predicting key determinants of impact, highlighting the power of these computational tools for ecological risk assessment. Beyond statistical modeling, mass spectrometry-based multi-omics approaches, including genomics, proteomics, lipidomics, and metabolomics provide essential systems-level insights into how ENMs alter microbial physiology and cellular pathways, revealing widespread adaptations and stress responses at multiple biological layers (<xref ref-type="bibr" rid="B53">Day et al., 2023</xref>). Community structure analysis further shows that ENMs, especially metal NPs, can profoundly disrupt microbial populations, diminishing critical functions like nutrient cycling and pollutant degradation by suppressing enzymatic activities.</p>
<p>Despite the robustness of these methodological frameworks, significant variability across studies underscores the need for standardized protocols. Differences in ENM types, doses, exposure durations, microbial communities, and omics platforms often limit comparability and reproducibility. Addressing this heterogeneity through harmonized experimental designs and cross-laboratory validation will be crucial to ensure consistent and reliable assessments of ENM-induced ecological risks across diverse environments.</p>
<sec id="s6-1">
<label>6.1</label>
<title>Marker gene sequencing for microbiome analysis</title>
<p>Marker gene sequencing is a widely used and cost-effective approach in microbiome analysis that targets conserved genetic regions (e.g., 16S rRNA for bacteria and archaea, ITS for fungi, 18S rRNA for eukaryotes) to profile microbial community composition and diversity (<xref ref-type="fig" rid="F3">Figure 3</xref>). This technique enables identification and relative quantification of taxa within complex microbial ecosystems by amplifying and sequencing these phylogenetic markers. It provides insights into taxonomic structure but has limited resolution for functional and strain-level analysis compared to whole metagenome sequencing (<xref ref-type="bibr" rid="B55">De la Cuesta-Zuluaga and Escobar, 2016</xref>; <xref ref-type="bibr" rid="B66">Douglas et al., 2018</xref>; <xref ref-type="bibr" rid="B111">Johnson et al., 2019</xref>; <xref ref-type="bibr" rid="B79">Galloway-Pe&#xf1;a and Hanson, 2020</xref>; <xref ref-type="bibr" rid="B19">Bharti and Grimm, 2021</xref>).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>General workflow for marker gene sequencing in microbiome analysis. The schematic outlines the traditional metagenomics workflow using amplicon sequencing of marker genes (16S rRNA for bacteria/archaea, 18S rRNA for eukaryotes, and ITS for fungi). Key steps include DNA extraction, amplification of target regions, high-throughput sequencing, and bioinformatics analysis for taxonomic profiling and diversity assessment.</p>
</caption>
<graphic xlink:href="fnano-07-1666431-g003.tif">
<alt-text content-type="machine-generated">Flowchart illustrating a marker gene sequencing process for microbiome analysis. Steps include sample collection, DNA extraction, amplification of marker gene, amplicon quality check and purification, library preparation, high-throughput sequencing, data quality control, sequence clustering, taxonomic assignment and diversity analysis, and statistical and functional inference. Each step is represented by a colored box with arrows indicating sequence progress.</alt-text>
</graphic>
</fig>
<sec id="s6-1-1">
<label>6.1.1</label>
<title>16S ribosomal RNA (rRNA) gene sequencing</title>
<p>16S rRNA gene sequencing is a cornerstone method for profiling bacterial and archaeal communities by targeting conserved and hypervariable regions (e.g., V1&#x2013;V2, V3&#x2013;V4, V4&#x2013;V5) of the &#x223c;1,500&#xa0;bp 16S gene. Primer choice such as V3&#x2013;V4 for broad bacterial coverage or V1&#x2013;V2 for higher species resolution is critical to capture the desired taxonomic groups accurately (<xref ref-type="bibr" rid="B168">Na et al., 2023</xref>; <xref ref-type="bibr" rid="B46">Combrink et al., 2023</xref>; <xref ref-type="bibr" rid="B133">Lee et al., 2023</xref>). Post-sequencing, raw reads undergo quality filtering, chimera removal, and demultiplexing using pipelines like QIIME 2 or Mothur (<xref ref-type="bibr" rid="B79">Galloway-Pe&#xf1;a and Hanson, 2020</xref>; <xref ref-type="bibr" rid="B46">Combrink et al., 2023</xref>; <xref ref-type="bibr" rid="B134">Lewis et al., 2021</xref>). Feature tables can be generated as Operational Taxonomic Units (OTUs) by clustering at &#x223c;97% similarity which is effective for legacy comparisons and mitigating sequencing noise, or as Amplicon Sequence Variants (ASVs) <italic>via</italic> denoising tools like DADA2 for single-nucleotide resolution, improved reproducibility, and finer ecological insights (<xref ref-type="bibr" rid="B79">Galloway-Pe&#xf1;a and Hanson, 2020</xref>; <xref ref-type="bibr" rid="B134">Lewis et al., 2021</xref>; <xref ref-type="bibr" rid="B109">Jeske and Gallert, 2022</xref>; <xref ref-type="bibr" rid="B43">Chiarello et al., 2022</xref>; <xref ref-type="bibr" rid="B50">Daly et al., 2024</xref>). Finally, taxonomic assignment is performed against curated databases (e.g., SILVA, Greengenes) and downstream analyses include diversity metrics and phylogenetic comparisons to reveal community structure and dynamics (<xref ref-type="fig" rid="F3">Figure 3</xref>) (<xref ref-type="bibr" rid="B111">Johnson et al., 2019</xref>; <xref ref-type="bibr" rid="B134">Lewis et al., 2021</xref>; <xref ref-type="bibr" rid="B46">Combrink et al., 2023</xref>).</p>
<p>Using 16S rRNA gene sequencing targeting the V3&#x2013;V4 region, a study revealed that long-term dietary exposure to Ag, SiO<sub>2</sub>, and TiO<sub>2</sub> NPs significantly altered the gut microbiota composition and &#x3b2;-diversity in mice. ASV analysis using DADA2 method showed a dose-dependent increase in Cyanobacteria and a marked reduction in Tenericutes and <italic>Turicibacter</italic> with TiO<sub>2</sub> NPs, while SiO<sub>2</sub> and TiO<sub>2</sub> also suppressed SCFA production. These shifts in microbial composition and metabolic function were largely reversible after an 8-week recovery period without NP exposure, indicating transient but notable perturbations of the gut microbiome by dietary NMs (<xref ref-type="bibr" rid="B183">Perez et al., 2021</xref>). Another research employed 16S rRNA gene sequencing (targeting V1&#x2013;V3 regions with 27f/534r primers) to investigate the influence of plant-derived nanoparticles on the gut microbiome of germ-free mice colonized with human fecal bacteria. Sequencing on the 454 Jr. platform and QIIME 2-based analysis revealed significant shifts in microbiota composition upon NP exposure, with notable enrichment of <italic>Lachnospiraceae</italic>, <italic>Bacteroidaceae</italic>, <italic>Coriobacteriaceae</italic>, and <italic>Ruminococcaceae</italic> families. OTUs were clustered at 97% similarity, and hierarchical clustering highlighted differences between <italic>in vitro</italic> and <italic>in vivo</italic> bacterial uptake of plant-derived nanoparticles, suggesting these NPs selectively modulate gut microbial communities and may alter functional pathways (<xref ref-type="bibr" rid="B237">Teng et al., 2025</xref>). Further, 16S rRNA gene sequencing revealed that oral exposure to SiO<sub>2</sub>NPs in young mice significantly altered gut microbiota composition and diversity, with increased abundances of <italic>Firmicutes</italic> and <italic>Patescibacteria</italic> and distinct shifts in &#x3b2;-diversity profiles. OTU-based analysis (97% similarity) and LEfSe identified 41 bacterial clades with differential abundance, suggesting SiO<sub>2</sub>NP-induced microbiome dysbiosis, which was associated with neurobehavioral impairments <italic>via</italic> disruption of the gut&#x2013;brain axis (<xref ref-type="bibr" rid="B58">Diao et al., 2021</xref>). Oral exposure to lead-based (CsPbBr<sub>3</sub>) perovskite nanoparticles (CPB-PNPs) induced significant, dose-dependent alterations in gut microbiota composition as revealed by 16S rRNA gene sequencing. ASV-based analysis showed reduced alpha diversity indices (Chao1, Shannon, Simpson) and a marked shift in &#x3b2;-diversity, as evidenced by principal coordinate analysis (PCoA). High-dose CPB-PNPs increased pro-inflammatory taxa such as <italic>Clostridia</italic> and decreased beneficial <italic>Muribaculaceae</italic>, disrupting the <italic>Firmicutes</italic>/<italic>Bacteroidetes</italic> ratio. Differential abundance analysis further identified enrichment of microbial taxa linked to intestinal inflammation. These microbiota perturbations were associated with compromised gut barrier integrity and colitis-like phenotypes in exposed mice (<xref ref-type="bibr" rid="B155">Mei et al., 2023</xref>).</p>
</sec>
<sec id="s6-1-2">
<label>6.1.2</label>
<title>18S rRNA and internal transcribed spacer (ITS) sequencing</title>
<p>18S rRNA and ITS amplicon sequencing are pivotal techniques for profiling fungal and other eukaryotic communities in microbiome studies (<xref ref-type="fig" rid="F3">Figure 3</xref>). The 18S rRNA gene, with its conserved and hypervariable regions (V1&#x2013;V9), enables broad phylogenetic placement across diverse eukaryotes, though it typically resolves taxa only down to genus level. In contrast, the ITS regions (ITS1 and ITS2), located between 18S, 5.8S, and 28S genes, exhibit high variability and are therefore standard markers for species- and strain-level identification of fungi (<xref ref-type="bibr" rid="B13">Banos et al., 2018</xref>; <xref ref-type="bibr" rid="B82">Gao et al., 2021</xref>; <xref ref-type="bibr" rid="B173">Olivier et al., 2023</xref>). These amplicon data are processed through pipelines like QIIME 2, LotuS2, or ITSx, which include quality filtering, chimera removal, OTU/ASV clustering, and taxonomic assignment using curated databases such as SILVA for 18S and UNITE for ITS (<xref ref-type="bibr" rid="B82">Gao et al., 2021</xref>; <xref ref-type="bibr" rid="B177">&#xd6;zkurt et al., 2022</xref>). This dual-marker approach offers comprehensive insights into eukaryotic microbiome structure and diversity. Using long-read sequencing of the nearly complete rRNA operon (16S-ITS-23S), a clear enhancement in species-level resolution of <italic>Lactobacillaceae</italic> has been reported compared to shorter amplicons. RibDif2 analysis revealed substantial allele overlap in V3&#x2013;V4 (n &#x3d; 43 overlaps) and whole 16S (&#x223c;11), while complete 16S-ITS-23S showed zero predicted overlaps. Empirical MinION&#x2122; data confirmed these predictions: full-length operon sequencing identified 100% of target species with fewer misclassifications, outperforming both V3&#x2013;V4 (80% correct) and single 16S (&#x223c;95%), thus highlighting the combined power of 18S rRNA/ITS region (rRNA operon) for accurate microbiome profiling (<xref ref-type="bibr" rid="B173">Olivier et al., 2023</xref>).</p>
<p>Most of the available reports focused on 16S rRNA gene sequencing to track bacterial community changes, and responses of eukaryotic microbes (fungi, protozoa) <italic>via</italic> 18S/ITS remains largely unexplored in NP exposure contexts. Using 16S and 18S rRNA gene sequencing with PNA clamps and ITS qPCR, a study demonstrated that nanoscale sulfur (pristine and stearic acid-coated) modulated both bacterial and fungal communities in the tomato rhizosphere. While bacterial ASV diversity increased under nano-sulfur treatments, eukaryotic communities, particularly fungi and ciliates, showed resilience with minimal diversity shifts. ITS qPCR revealed no significant changes in total fungal abundance, but differential analysis indicated reduced relative abundance of <italic>Fusarium oxysporum</italic> in nano-sulfur treatments compared to controls. Enrichment of sulfur-oxidizing bacteria (<italic>Thiobacillus</italic>) and subtle shifts in fungal taxa suggest nano-sulfur may suppress soil-borne pathogens indirectly by altering microbiome composition and functional interactions (<xref ref-type="bibr" rid="B229">Steven et al., 2024</xref>).</p>
</sec>
</sec>
<sec id="s6-2">
<label>6.2</label>
<title>Whole-genome shotgun (WGS) metagenomics</title>
<p>Whole-Genome Shotgun (WGS) metagenomics is an untargeted sequencing method that captures the entire genetic content of all microorganisms in a sample that include bacteria, archaea, fungi, viruses, and eukaryotes, providing comprehensive taxonomic and functional insights. Compared to 16S rRNA amplicon sequencing, WGS delivers higher species- and strain-level resolution, detects greater microbial diversity, and identifies functional genes such as antibiotic resistance and metabolic pathways (<xref ref-type="bibr" rid="B198">Ranjan et al., 2016</xref>; <xref ref-type="bibr" rid="B112">Jovel et al., 2016</xref>; <xref ref-type="bibr" rid="B117">Keepers et al., 2019</xref>; <xref ref-type="bibr" rid="B25">Brumfield et al., 2020</xref>). However, it is more expensive, requires deeper sequencing coverage, and demands advanced computational infrastructure due to large data volumes and complexity (<xref ref-type="bibr" rid="B112">Jovel et al., 2016</xref>; <xref ref-type="bibr" rid="B76">Fox et al., 2024</xref>). WGS metagenomics offers a powerful, holistic view of microbial communities and their functional potential, making it indispensable for studies that extend beyond taxonomic profiling into functional and ecological questions.</p>
<p>WGS metagenomics begins with sample collection and total DNA extraction, followed by random fragmentation and high-throughput sequencing (e.g., Illumina, PacBio, Nanopore). After quality control and contaminant removal (using tools like FastQC and Trimmomatic), reads are assembled <italic>de novo</italic> into contigs and binned into putative genomes (MAGs) using assemblers (e.g., MEGAHIT, metaSPAdes) and binning tools (e.g., MetaBAT, CONCOCT). These assemblies and unassembled reads are then annotated taxonomically (with tools like Kraken2, GTDB-Tk for MAGs, or Kraken2, MetaPhlAn for reads) and functionally profiled against databases such as KEGG, COG, eggNOG, and CARD to reveal metabolic pathways and resistance genes (<xref ref-type="bibr" rid="B184">P&#xe9;rez-Cobas et al., 2020</xref>; <xref ref-type="bibr" rid="B19">Bharti and Grimm, 2021</xref>; <xref ref-type="bibr" rid="B212">Saenz et al., 2022</xref>). The final step involves comparing taxonomic and functional profiles across samples to assess microbial diversity, community structure, and functional potential (<xref ref-type="fig" rid="F4">Figure 4</xref>).</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>General workflow for whole genome shotgun (WGS) metagenomics in microbiome analysis. The schematic illustrates the WGS metagenomics workflow starting from sample collection and total DNA extraction, followed by random fragmentation, library preparation, and high-throughput sequencing (e.g., Illumina, PacBio, Nanopore). Quality control and contaminant removal (using tools such as FastQC and Trimmomatic) are performed before downstream analysis. Two pathways are depicted: the assembly-based pathway involves <italic>de novo</italic> assembly (MEGAHIT, metaSPAdes), binning (MetaBAT, CONCOCT), and taxonomic annotation (GTDB-Tk); the read-based pathway uses direct profiling tools (Kraken2, MetaPhlAn). Both approaches undergo functional annotation (KEGG, COG, eggNOG, CARD) to generate taxonomic and functional profiles, supporting comparative analyses of microbial diversity, community structure, and functional potentials across samples.</p>
</caption>
<graphic xlink:href="fnano-07-1666431-g004.tif">
<alt-text content-type="machine-generated">Flowchart depicting the process of whole genome shotgun (WGS) metagenomics from sample collection to analysis in microbiome studies. Steps include DNA extraction, fragmentation, and library preparation, raw read generation, and quality control. Two pathways are shown: Assembly Pathway and Read-Based Pathway. The Assembly Pathway involves de novo assembly and contig quality check, leading to taxonomic annotation. The Read-Based Pathway involves direct profiling. Both pathways proceed to functional annotation and generate taxonomic and functional profiles, enabling comparative analysis across samples for taxonomic diversity, community structure, and functional potential assessment.</alt-text>
</graphic>
</fig>
<p>WGS metagenomics and traditional metagenomics (e.g., amplicon sequencing of marker genes like 16S, 18S, or ITS) both aim to profile microbial communities, but they differ fundamentally in scope and resolution. WGS metagenomics sequences all DNA fragments randomly, enabling species- and strain-level identification, comprehensive detection of bacteria, archaea, fungi, viruses, and functional gene content including antibiotic resistance and metabolic pathways. In contrast, marker gene-based metagenomics targets specific loci (like 16S, 18S, ITS) to characterize community composition more cost-effectively and with simpler bioinformatics, though typically limited to genus-level resolution and offering limited insight into functional potential. While WGS metagenomics demands deeper sequencing, greater computational resources, and more complex analysis pipelines, it reveals richer diversity including rare taxa and accurate functional profiling, making it ideal for comprehensive ecological or clinical microbiome studies (<xref ref-type="bibr" rid="B198">Ranjan et al., 2016</xref>; <xref ref-type="bibr" rid="B199">Rausch et al., 2019</xref>; <xref ref-type="bibr" rid="B25">Brumfield et al., 2020</xref>; <xref ref-type="bibr" rid="B184">P&#xe9;rez-Cobas et al., 2020</xref>; <xref ref-type="bibr" rid="B258">Wang Z. et al., 2023</xref>).</p>
<p>Whole-genome shotgun metagenomics revealed that ZnO NPs significantly altered soil microbial taxonomic and functional diversity, reducing gene abundance related to carbon degradation and nitrogen cycling while increasing genes for CO<sub>2</sub> fixation and sulfur metabolism. ZnO NPs also disrupted microbial network complexity by decreasing connectivity and modularity among taxa, with archaeal, fungal, and viral communities showing more pronounced responses than bacteria (<xref ref-type="bibr" rid="B233">Sun et al., 2025</xref>). Additionally, WGS metagenomic profiling of nano-ZnO&#x2013;polluted soils revealed a dose-dependent enrichment of biofilm-related genes, particularly those involved in exopolysaccharide biosynthesis and cell attachment, with stronger effects seen for nanoparticles than bulk ZnO at moderate concentrations (50&#x2013;500&#xa0;mg/kg) (<xref ref-type="bibr" rid="B62">Dinesh et al., 2023b</xref>). Further, multidrug resistance genes and mobile genetic elements (MGEs) co-occurred with biofilm genes, indicating enhanced potential for horizontal gene transfer under nano-ZnO exposure (<xref ref-type="bibr" rid="B61">Dinesh et al., 2023a</xref>). At higher ZnO levels (&#x2265;500&#xa0;mg/kg), nano-ZnO suppressed microbial biomass, respiration, and enzyme activity, reflecting microbial stress and community destabilization (<xref ref-type="bibr" rid="B62">Dinesh et al., 2023b</xref>). These findings underscore that nano-ZnO can reshape soil microbiome function and resistance dynamics <italic>via</italic> gene-level shifts in stress response and community interaction mechanisms. WGS metagenomic analysis of wastewater microbial communities exposed to gold NPs revealed that NP morphology (nanospheres vs. nanorods) strongly influenced both taxonomic composition and functional gene profiles. CTAB-coated nanospheres caused significant shifts in microbial structure and enriched antibiotic resistance genes, metal resistance genes, and plasmid-associated genes, whereas nanorods had subtler effects. These results highlight how NP design parameters can modulate microbiome diversity and functional potential in engineered ecosystems (<xref ref-type="bibr" rid="B158">Metch et al., 2018</xref>).</p>
<p>Therefore, both WGS metagenomic analysis and traditional marker-based metagenomics using next-generation sequencing provide culture-independent approaches to comprehensively characterize the human gut microbiome and environmental microbial communities. These methods enable the detection of dysbiosis, detailed taxonomic profiling, and the discovery of novel functional genes and metabolic pathways, including those associated with health, disease, and the resistome. Despite these advances, challenges remain. High-throughput sequencing (HTS) data quality can be compromised by sequencing errors, sampling bias, and variable 16S copy number across taxa&#x2014;factors that skew abundance and diversity estimates (<xref ref-type="bibr" rid="B118">Kembel et al., 2012</xref>; <xref ref-type="bibr" rid="B57">Di Bella et al., 2013</xref>; <xref ref-type="bibr" rid="B119">Khachatryan et al., 2020</xref>; <xref ref-type="bibr" rid="B17">Beaudry et al., 2021</xref>; <xref ref-type="bibr" rid="B76">Fox et al., 2024</xref>). Moreover, the rapid growth of sequencing data demands continuous development of scalable, reproducible, and integrative bioinformatics frameworks to keep pace with analytical needs. Continued innovation in HTS technologies and computational tools will be critical to unlocking the full potential of microbiome science in both environmental and biomedical contexts.</p>
</sec>
<sec id="s6-3">
<label>6.3</label>
<title>Metaproteomics for microbiome analysis</title>
<p>Metaproteomics is a powerful, culture-independent approach for microbiome analysis that investigates the entire protein complement expressed by complex microbial communities in their native environment. Starting from biomass-enriched samples (e.g., feces, soil), proteins are extracted, digested into peptides (commonly <italic>via</italic> phenol extraction and FASP protocols), and then analyzed using LC&#x2013;MS/MS (<xref ref-type="bibr" rid="B234">Tanca et al., 2014</xref>; <xref ref-type="bibr" rid="B287">Zhang et al., 2016</xref>; <xref ref-type="bibr" rid="B98">Heyer et al., 2019</xref>; <xref ref-type="bibr" rid="B65">Do et al., 2024</xref>). This workflow enables identification of active microbial species and their expressed enzymes, revealing metabolic pathways and biomarkers linked to community function such as over 600 microbial species and 250 protein families in gut samples (<xref ref-type="bibr" rid="B234">Tanca et al., 2014</xref>; <xref ref-type="bibr" rid="B98">Heyer et al., 2019</xref>; <xref ref-type="bibr" rid="B99">2025</xref>). Bioinformatic tools like MetaProteomeAnalyzer, MaxQuant, and Unipept facilitate peptide-spectrum matching, taxonomic and functional annotation, and robust protein quantification (<xref ref-type="bibr" rid="B228">Starr et al., 2018</xref>; <xref ref-type="bibr" rid="B123">Kruk et al., 2024</xref>; <xref ref-type="bibr" rid="B65">Do et al., 2024</xref>; <xref ref-type="bibr" rid="B170">Nebauer et al., 2024</xref>). When combined with metagenomics or metatranscriptomics, metaproteomics offers a holistic view of microbial activity, host&#x2013;microbe interactions, and ecosystem dynamics, advancing both research and diagnostic applications (<xref ref-type="bibr" rid="B99">Heyer et al., 2025</xref>). Metaproteomics, which analyzes the expressed proteins of microbial communities, provides a direct snapshot of active biological processes; improvements in mass spectrometry and bioinformatics have enhanced the ability to profile functional shifts within microbiomes (<xref ref-type="bibr" rid="B107">Jagtap et al., 2015</xref>; <xref ref-type="bibr" rid="B280">Young et al., 2015</xref>; <xref ref-type="bibr" rid="B288">Zhang X. et al., 2018</xref>; <xref ref-type="bibr" rid="B65">Do et al., 2024</xref>; <xref ref-type="bibr" rid="B248">Vald&#xe9;s-Mas et al., 2025</xref>).</p>
<p>While significant progress has been made in understanding NM&#x2013;microbiome interactions using approaches such as 16S/18S rRNA amplicon sequencing for taxonomic profiling, WGS metagenomics for functional gene prediction, and culture-based assays for targeted microbial analyses, these methods offer only partial insights into microbial function. Notably, metaproteomics, a powerful tool capable of directly assessing protein-level responses, microbial activity, stress adaptations, and metabolic pathway alterations in complex communities, remains largely absent in this field. This represents a critical research gap, as integrating metaproteomics could provide a more comprehensive understanding of how NMs influence microbiome functionality beyond genetic potential, capturing real-time microbial responses to NP exposure. By integrating metagenomic sequencing with fecal proteomics, <xref ref-type="bibr" rid="B248">Vald&#xe9;s-Mas et al. (2025)</xref> applied metagenome-informed metaproteomics (MIM) to both mouse models and human IBD patients, enabling species-level resolution of host&#x2013;microbiome&#x2013;diet interactions. In IBD cases, they uncovered a dual signature of &#x201c;compositional dysbiosis&#x201d; <italic>i.e.</italic>, shifts in microbial taxa and &#x201c;functional dysbiosis&#x201d; <italic>i.e.</italic>, reduced protein activity from beneficial commensals in response to inflammatory signals. MIM also accurately reconstructed dietary exposure profiles and <italic>in vivo</italic> nutritional compliance using dietary-specific protein markers. Utilizing microbiome transfer experiments, the study revealed early-onset, species-specific microbiome and host proteomic responses, and identified candidate fecal host-microbiome protein biomarkers that outperformed traditional calprotectin (S100A8/S100A9) in predicting IBD (<xref ref-type="bibr" rid="B248">Vald&#xe9;s-Mas et al., 2025</xref>). These findings demonstrate that a combined dietary&#x2013;microbial&#x2013;host proteomic analysis can functionally dissect trans-kingdom interactions and offers advancements toward personalized diagnostics and therapeutics in gut-related diseases.</p>
</sec>
<sec id="s6-4">
<label>6.4</label>
<title>Metabolomics in microbiome analysis</title>
<p>Metabolomics in microbiome analysis employs techniques like LC&#x2013;MS, GC&#x2013;MS, and NMR to profile small molecules (metabolites) produced or transformed by microbial communities, offering a direct snapshot of microbial activity, biochemical interactions, and signaling. By illuminating changes in metabolic pathways such as SCFA production, amino acid metabolism, energy metabolism or xenobiotic transformations, metabolomics complements genomic and transcriptomic data to reveal functional and ecological impacts of microbiota under different conditions. Metabolomics begins with strategic experimental design followed by sample collection and rapid quenching to preserve metabolic states, then extraction of metabolites using solvents (e.g., methanol, acetone, chloroform) optimized for polarity range. Extracted metabolites are analyzed <italic>via</italic> LC&#x2013;MS, GC&#x2013;MS, or NMR, allowing separation and detection of wide-ranging compounds with sensitivity and structural resolution. Raw data undergo preprocessing including noise reduction, peak detection, retention time alignment, and normalization using tools like XCMS, MZmine, and MS-DIAL. Metabolite identification is achieved through spectral database matching (e.g., HMDB, METLIN), followed by statistical analysis (PCA, PLS-DA) and pathway enrichment (KEGG, MetaboAnalyst) to interpret biological significance (<xref ref-type="bibr" rid="B125">Kumar et al., 2020</xref>; <xref ref-type="bibr" rid="B93">Han et al., 2021</xref>; <xref ref-type="bibr" rid="B40">Chen Y. et al., 2022</xref>; <xref ref-type="bibr" rid="B167">Muhamadali et al., 2023</xref>).</p>
<p>Untargeted metabolomics revealed that TiO<sub>2</sub> NPs inhibited growth of key beneficial bacteria (<italic>L. reuteri</italic>, <italic>L. gasseri</italic>, <italic>B. animalis</italic>, <italic>B. longum</italic>) through membrane damage and disrupted metabolic pathways, including tryptophan and arginine metabolism <italic>in vitro</italic>. <italic>In vivo</italic>, mice fed with TiO<sub>2</sub> NPs showed altered urinary metabolite profiles, notably reduced neuroprotective metabolites and perturbed tryptophan metabolism, all indicative of gut microbiome&#x2013;mediated host metabolic dysregulation (<xref ref-type="bibr" rid="B266">Wu et al., 2023</xref>). Studies integrating microbiome profiling with metabolomic analysis have shown that ZnO NPs (25&#x2013;100&#xa0;mg/kg in poultry) significantly disrupt gut microbial community structure and metabolism. Metabolomic shifts included altered levels of glucose, choline, lactate, methionine, indole derivatives, and pro-inflammatory arachidonic acid metabolites correlating with declines in beneficial taxa like <italic>Lactobacillus</italic> and <italic>Bifidobacterium</italic>, and increased <italic>E</italic>. <italic>coli</italic> and other opportunists. These multi-omics approaches reveal that NM exposure can rewire host&#x2013;microbe metabolic interactions, with implications for inflammatory and metabolic health (<xref ref-type="bibr" rid="B74">Feng et al., 2017</xref>). In an <italic>in vitro</italic> digestion and fermentation model, ZnO, TiO<sub>2</sub>, and Ag NPs induced significant shifts in gut microbial genera, particularly <italic>Bifidobacterium</italic>, <italic>Sutterella</italic>, <italic>Escherichia</italic>, and <italic>Bacteroides</italic> as determined by 16S rRNA sequencing. Metabolomic profiling revealed NP-specific modulation of metabolites, including indole derivatives, peptides, and protein metabolism intermediates, with TiO<sub>2</sub> notably increasing pro-inflammatory arachidonic acid pathway metabolites like prostaglandin E<sub>2</sub> and leukotriene B<sub>4</sub>. These findings suggest that metallic NPs exposure can disrupt both microbial composition and metabolic by-products linked to gut inflammation and disease pathways (<xref ref-type="bibr" rid="B247">Vaccari et al., 2023</xref>). Oral exposure to Ag NPs and silver nanowires (Ag NWs) at 0.5&#x2013;2.5&#xa0;mg/kg in mice significantly disrupted gut microbiota structure reducing diversity and suppressing Gram-negative bacteria within 14&#xa0;days, while the community largely recovered by 28&#xa0;days. Despite this recovery, fecal and systemic metabolomics revealed persistent increases in gut-derived 1H-indole-3-carboxylic acid and elevated gut and blood serotonin levels, linking NPs exposure to microbial metabolic shifts and neurochemical alterations (<xref ref-type="bibr" rid="B259">Wang X. et al., 2023</xref>). Therefore, for microbiome studies, metabolomics insights alone or preferably integrated with metagenomics, metatranscriptomics, or metaproteomics data can be useful to uncover mechanistic links between microbial composition, metabolic activity, and environmental or host interactions.</p>
<p>Together, these <italic>meta-omics</italic> technologies transcend traditional culture-based methods, enabling comprehensive analysis of microbial species, functional capacity, and metabolic activity in relation to health and disease. However, despite their power, challenges remain in data integration and interpretation. The sheer complexity of meta-omics datasets necessitates robust bioinformatics frameworks and harmonized analytical standards to fully leverage these approaches in microbiome-targeted therapies and precision medicine (<xref ref-type="bibr" rid="B255">Wang et al., 2015</xref>; <xref ref-type="bibr" rid="B192">Puig-Castellvi et al., 2023</xref>; <xref ref-type="bibr" rid="B65">Do et al., 2024</xref>).</p>
</sec>
<sec id="s6-5">
<label>6.5</label>
<title>Use of <italic>in vitro</italic> models and <italic>in vivo</italic> animal studies</title>
<p>
<italic>In Vitro</italic> Colon Simulators (e.g., SHIME&#xae;, TIM-2, CoMiniGut, SIMGI) are dynamic, multi-stage fermentation systems that faithfully reproduce human colonic conditions and microbial ecosystems. For ENM&#x2013;microbiome interaction studies, they offer unparalleled ability to simulate realistic dosing, track microbiota and metabolite alterations, and integrate with host-response models making them an essential tool in assessing NMs safety and biological impact in the gut. Using a dynamic, multi-stage <italic>in vitro</italic> colon simulator inoculated with human fecal microbiota, <xref ref-type="bibr" rid="B289">Zhang et al. (2021)</xref> demonstrated that exposure to nano-ZnO caused dose-dependent declines in SCFA production and significant perturbations in microbial composition and diversity. Following cessation of exposure, microbial diversity largely rebounded; however, SCFA levels remained suppressed in relation to ZnO concentration. Moreover, the study revealed contrasting effects on the gut resistome: a medium concentration (2.5&#xa0;mg/L) reduced the abundance of many antibiotic-resistance genes, whereas a low concentration (0.1&#xa0;mg/L) notably enriched tetracycline resistance genes (<xref ref-type="bibr" rid="B289">Zhang et al., 2021</xref>).</p>
<p>Intestinal organoids and gut-on-chip systems as <italic>in vitro</italic> models and <italic>in vivo</italic> animal models together provide a complementary and powerful framework for evaluating how ENMs interact with and impact the microbiome, with valuable insights for human health risk assessment. Human intestinal organoids, derived from stem cells and often cultured within biomimetic hydrogels or perfusable microfluidic platforms, offer improved physiological relevance over 2D cultures for investigating NM&#x2013;microbiome interactions in the gut. These 3D structures faithfully recapitulate crypt&#x2013;villus architecture and cellular diversity including enterocytes, goblet cells, Paneth cells, and M&#xa0;cells&#x2014;enabling physiologically relevant assessments of nanotoxicity and uptake dynamics (<xref ref-type="bibr" rid="B190">Prasad et al., 2021</xref>; <xref ref-type="bibr" rid="B14">Bantun et al., 2022</xref>; <xref ref-type="bibr" rid="B284">Yuan and Liu, 2023</xref>; <xref ref-type="bibr" rid="B220">Shi et al., 2024</xref>). When co-cultured with microbiota, they reveal critical insights into cross-kingdom metabolism: for instance, gut microbes have been shown to enzymatically degrade CNMs (e.g., GO, SWCNTs), fermenting them into butyrate, which then modulates epithelial stem cell proliferation and barrier integrity (<xref ref-type="bibr" rid="B49">Cui et al., 2023</xref>). Moreover, exposure to nanoplastics or engineered inorganic nanoparticles triggers inflammatory signaling in organoids, particularly through M cell-mediated pathways and disrupts commensal composition by altering the <italic>Firmicutes/Bacteroidetes</italic> ratio, with downstream effects on mucus secretion and mucosal immunity (<xref ref-type="bibr" rid="B95">Hao et al., 2022</xref>; <xref ref-type="bibr" rid="B193">Qiao et al., 2024</xref>). A study aimed to elucidate how nano-sized food additives interact with commensal and pathogenic bacteria within the gastrointestinal tract utilized human gastric organoids to demonstrate that silica NP&#x2013;<italic>H. pylori</italic> complexes retained bacterial adherence but significantly attenuated bacterial internalization and pathogenic signaling, including CagA phosphorylation and IL-8 secretion. These findings underscore the potential of ENMs to modulate host&#x2013;microbiome interactions within the gastric niche (<xref ref-type="bibr" rid="B222">Siemer et al., 2018</xref>).</p>
<p>Gut-on-chip platforms are microfluidic devices that reconstitute key physiological and structural aspects of the human intestine such as epithelial villi, mucus layers, and peristaltic flow, while enabling co-culture with microbial communities under controlled, real-time conditions (<xref ref-type="bibr" rid="B242">Trujillo-de Santiago et al., 2018</xref>; <xref ref-type="bibr" rid="B268">Xiang et al., 2020</xref>; <xref ref-type="bibr" rid="B238">Thomas et al., 2023</xref>). These systems allow precise dosing of ENMs and measurement of outcomes like barrier integrity, cytokine production, microbial colonization, and metabolite exchange. Gut-on-chip models are faster and free from ethical issues than animal studies, making them ideal for high-throughput screening of nanoparticles and their acute effects on gut&#x2013;microbe interactions.</p>
<p>
<italic>In vivo</italic> animal models, particularly zebrafish and rodents, offer critical physiological and systemic context for assessing long-term effects of ENM exposure capturing microbiome perturbations, immune modulation, metabolic shifts, and organ-level responses. Zebrafish are especially valuable as high-throughput vertebrate models due to their conserved intestinal physiology, genetic tractability, and amenability to germ-free and fluorescent-transgenic approaches, enabling real-time visualization of host&#x2013;microbe&#x2013;ENM interactions (<xref ref-type="bibr" rid="B267">Xia et al., 2022</xref>). Rodent studies, while resource-intensive and ethically demanding, complement these findings by providing detailed insights into ENM-induced shifts in microbial communities, metabolite profiles, inflammatory markers, and histopathology across tissues. However, these <italic>in vivo</italic> approaches require careful design to balance throughput, ethical considerations, and translational relevance (e.g., dosing regimen, exposure duration), underscoring the need for integrated strategies that leverage both zebrafish and murine models (<xref ref-type="bibr" rid="B10">Ashammakhi et al., 2020</xref>; <xref ref-type="bibr" rid="B267">Xia et al., 2022</xref>; <xref ref-type="bibr" rid="B295">Zhong et al., 2022</xref>; <xref ref-type="bibr" rid="B143">Liu et al., 2024</xref>).</p>
<p>However, both models have limitations. Gut-on-chip systems lack full immune and multi-organ integration and are best suited for mechanistic, short-term investigations. Animal studies provide whole-body responses but are less amenable to mechanistic dissection and suffer from inter-species variability. Thus, a hybrid strategy using gut-on-chip platforms for mechanistic hypothesis testing followed by targeted validation in animal models offers a robust pathway to translate findings to human-relevant insights. By standardizing ENM dosing, dynamic microenvironment conditions, co-culture complexity, and integrated omics readouts, the synergy between these approaches will enable safer ENM development and improved prediction of their microbiome-related effects.</p>
</sec>
</sec>
<sec id="s7">
<label>7</label>
<title>Risk assessment and long-term implications</title>
<p>Assessing the risks and long-term implications of ENMs on microbiome interactions requires a robust, integrative approach combining cutting-edge tools, environmental and regulatory expertise. A global meta-analysis of over 2,100 observations has shown that ENMs negatively impact soil microbial diversity, biomass, and functional enzyme activities, with artificial intelligence models like random forests effectively predicting these outcomes based on ENM characteristics (<xref ref-type="bibr" rid="B188">Pietroiusti et al., 2016</xref>). To further elucidate these effects, multi-omics technologies such as metagenomics, metaproteomics, and metabolomics are increasingly being recommended by regulatory bodies, including the European Food Safety Authority (EFSA), to standardize microbiome assessments and identify biomarkers of disturbance under controlled exposure scenarios. For instance, mass spectrometry-based omics workflows enable comprehensive profiling of microbial functional responses to ENMs, revealing shifts in pathways linked to nutrient cycling and immune signaling (<xref ref-type="bibr" rid="B165">Mortimer et al., 2021</xref>).</p>
<p>Environmental and gut microbiome changes following ENM exposure evaluated through both acute (e.g., 90-day rodent studies) and long-term trials indicate persistent effects on gut barrier integrity, immune modulation, and SCFA production (<xref ref-type="bibr" rid="B188">Pietroiusti et al., 2016</xref>; <xref ref-type="bibr" rid="B108">Javurek et al., 2017</xref>; <xref ref-type="bibr" rid="B235">Tang et al., 2021</xref>; <xref ref-type="bibr" rid="B246">Utembe et al., 2022</xref>). Developmental exposure to AgNPs in mice resulted in persistent gut dysbiosis, characterized by reduced levels of beneficial taxa (<italic>Bifidobacterium</italic>, <italic>Mucispirillum</italic>) and enrichment of inflammatory-associated bacteria (<italic>Prevotella</italic>, <italic>Enterococcus</italic>). These microbiome alterations correlated with disruptions in metabolic pathways, reduced microglial counts in the brain, and behavioral and metabolic changes in offspring, highlighting the long-term impacts of early-life NMs exposure on the gut&#x2013;microbiome&#x2013;brain axis (<xref ref-type="bibr" rid="B145">Lyu et al., 2021</xref>). Moreover, emerging evidence indicates that CNMs can be fermented by gut bacteria into bioactive metabolites like butyrate, which then modulate host physiology, such as intestinal stem cell differentiation highlighting not only toxicological but also transformative microbial&#x2013;host interactions (<xref ref-type="bibr" rid="B49">Cui et al., 2023</xref>). Animal models are essential for capturing chronic, systemic effects, but high-throughput <italic>in vitro</italic> systems such as gut-on-chip platforms are increasingly integrated into tiered risk frameworks to enhance hazard identification without excessive animal use. These tiered strategies align with emerging regulatory recommendations that prioritize microbiome endpoints and make use of NAMs (new approach methodologies), standardized sampling, and shared microbiome databases to improve cross-study comparability and regulatory confidence (<xref ref-type="bibr" rid="B174">OP EUROPA, 2027</xref>).</p>
<p>While the impacts of ENMs on microbiome include dysbiosis, impaired function of key microbial taxa, altered host-microbe interactions, chronic gut inflammation, immune dysfunction, metabolic and neurological disorders, their roles as environmental disruptors remain under-evaluated (<xref ref-type="bibr" rid="B235">Tang et al., 2021</xref>; <xref ref-type="bibr" rid="B131">Lamas et al., 2020</xref>; <xref ref-type="bibr" rid="B140">Li P. et al., 2024</xref>). EFSA&#x2019;s roadmap emphasizes establishing core microbiome definitions, bioindicator panels, harmonized analytical protocols, and cross-lab networks to resolve this gap (<xref ref-type="bibr" rid="B56">Debode et al., 2024</xref>). Overall, advancing ENM risk assessment necessitates a combined strategy linking global meta-analyses, multi-omics, sophisticated modeling, and tiered experimental designs supported by regulatory-driven standardization and data sharing. This holistic approach promises more reliable prediction, monitoring, and mitigation of ENM effects on microbial ecosystems and public health.</p>
</sec>
<sec id="s8">
<label>8</label>
<title>Regulatory and mitigation strategies</title>
<p>Regulation of ENMs currently leverages existing legislative frameworks rather than relying on bespoke NM laws. In the United States, the Toxic Substances Control Act (TSCA) empowers the Environmental Protection Agency (EPA) to require pre-manufacture notices and implement information-gathering mandates for new nanoforms, while the Food and Drug Administration (FDA), the Occupational Safety and Health Administration (OSHA), and Consumer Product Safety Commission regulate ENMs in food, drugs, cosmetics, and workplaces under broader statutes and hazard communication standards (<xref ref-type="bibr" rid="B141">Lin, 2001</xref>; <xref ref-type="bibr" rid="B236">Tang et al., 2024</xref>; <xref ref-type="bibr" rid="B69">El-Kalliny et al., 2023</xref>; <xref ref-type="bibr" rid="B87">Ghosh and Kumar, 2024</xref>). The European Union (EU) employs Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) legislation, Classification, Labelling and Packaging (CLP) Regulation, and the Biocidal Products Regulation to enforce registration, hazard evaluation, and labeling of materials at or above one ton annually, and maintains transparency <italic>via</italic> national NM registries (e.g., France, Denmark, Norway, Belgium) and the EU Observatory for Nanomaterials (<xref ref-type="bibr" rid="B71">Environment EC, 2024b</xref>; <xref ref-type="bibr" rid="B70">Environment EC, 2024a</xref>; <xref ref-type="bibr" rid="B67">ECHA, 2025</xref>; <xref ref-type="bibr" rid="B181">Pavlicek et al., 2021</xref>). Standardization efforts led by international organizations like Organisation for Economic Co-operation and Development (OECD), International Organization for Standardization (ISO) Technical Committee (TC) 229 (ISO/TC 229), and World Health Organization (WHO) further support harmonized definitions, testing protocols, and &#x201c;precautionary approach&#x201d; workplace guidelines. Despite this multilayered oversight, challenges include fragmented global definitions, evolving physicochemical properties, detection limitations, and often a disconnect between innovation pace and regulation leading experts to call for adaptive, coordinated, and evidence-driven governance that leverages &#x201c;Safe-by-Design&#x201d; approaches and precautionary risk frameworks (<xref ref-type="bibr" rid="B89">Gottardo et al., 2021</xref>; <xref ref-type="bibr" rid="B122">Kraegeloh et al., 2018</xref>; <xref ref-type="bibr" rid="B202">Resnik, 2019</xref>; <xref ref-type="bibr" rid="B213">Salieri et al., 2021</xref>).</p>
<p>Mitigation strategies for ENM-associated risks follow a dual pathway: reducing hazard through material design and minimizing exposure across the life cycle. &#x201c;Safe-by-Design&#x201d; approaches actively tailor physicochemical properties such as size, shape, surface charge, encapsulation to improve stability and biocompatibility while limiting harmful byproducts (<xref ref-type="bibr" rid="B122">Kraegeloh et al., 2018</xref>). These principles are implemented in EU projects (e.g., NANoREG, NanoReg2, SUN, caLIBRAte) that integrate risk pre-assessment, modeling (QSAR, AOP pathways), iterative stakeholder engagement, and green synthesis to align early-stage innovation with safety and regulatory preparedness (<xref ref-type="bibr" rid="B122">Kraegeloh et al., 2018</xref>; <xref ref-type="bibr" rid="B105">Isigonis et al., 2019</xref>; <xref ref-type="bibr" rid="B215">Schmutz et al., 2020</xref>). On the operational front, occupational controls adhere to the hierarchy of hazard mitigation: elimination/substitution, engineering controls (e.g., HEPA-filtered hoods, gloveboxes, sealed balances), administrative best practices, and personal protective equipment as per WHO and OSHA guidance (<xref ref-type="bibr" rid="B175">OSHA, 2025</xref>; <xref ref-type="bibr" rid="B154">McLean et al., 2024</xref>). Environmental surveillance and risk assessment rely on life-cycle analyses, environmental monitoring, and computational evaluation to forecast fate, transport, and ecological impacts, while AI-augmented characterization and risk modeling promise faster assessments and reduced animal testing. Together, these approaches couple proactive material design with rigorous exposure controls to manage ENM risks to environmental and human microbiomes.</p>
</sec>
<sec id="s9">
<label>9</label>
<title>Future directions and research gaps</title>
<p>Future research on the impact of ENMs on microbiome interactions points toward several critical directions. Firstly, the field must advance standardized life-cycle exposure models that track ENMs from synthesis through environmental release, transformation, and biological uptake&#x2014;an area having significant research gap (e.g., bioaccumulation of transformation products) (<xref ref-type="bibr" rid="B188">Pietroiusti et al., 2016</xref>). Secondly, integrating <italic>in vitro</italic> and <italic>in vivo</italic> systems with multi-omics technologies (genomics, proteomics, metabolomics) and predictive machine learning that offers the promise of mechanistic insight and reliable ecological risk forecasting. For instance, recent meta-analyses and machine learning applications have effectively predicted ENM impacts on soil microbial communities and identified functional gene disruptions. Additionally, a One-Health research framework that encompasses soil, plant, animal, and human microbiomes is urgently needed to explore systemic ENM effects across ecological and host-associated networks. Furthermore, the identification of microbiome-based biomarkers such as shifts in SCFA profiles, immune-metabolite signatures, or specific community compositions could serve as early warnings of ENM-induced dysbiosis. Finally, establishing standardized protocols and NM research modules, shared data repositories, and inter-laboratory collaborations will be essential to ensure reproducibility, regulatory trust, and comprehensive understanding of long-term ENM&#x2013;microbiome interactions.</p>
</sec>
<sec sec-type="conclusion" id="s10">
<label>10</label>
<title>Conclusion</title>
<p>ENMs are transforming numerous industries due to their unique physicochemical properties, yet their interactions with microbial ecosystems raise significant ecological and health concerns. This review highlights the profound effects of ENMs on human-associated microbiota and environmental microbial communities, revealing their capacity to alter microbial diversity, metabolic activity, and functional roles in nutrient cycling and host health. Metal-based NPs, such as Ag, TiO<sub>2</sub>, ZnO, and CNMs, can induce dysbiosis, impair enzymatic activities critical for biogeochemical processes, and potentially accelerate the spread of antimicrobial resistance genes. While advanced methodologies like high-throughput sequencing, meta-omics approaches, and <italic>in vitro</italic>/<italic>in vivo</italic> models have deepened our understanding of ENM&#x2013;microbiome interactions, challenges persist in standardizing protocols and assessing long-term risks. Given the dual nature of ENMs, offering both technological advantages and potential ecological hazards, it is imperative to adopt a precautionary approach toward their deployment. Future research should focus on elucidating dose- and context-dependent effects, exploring safer-by-design NMs, and developing regulatory frameworks that account for microbiome sensitivity. Only through such multidisciplinary efforts we can ensure the sustainable use of nanotechnologies while preserving microbial diversity and ecosystem resilience.</p>
</sec>
</body>
<back>
<sec sec-type="author-contributions" id="s11">
<title>Author contributions</title>
<p>AC: Writing &#x2013; original draft, Writing &#x2013; review and editing. MG: Conceptualization, Writing &#x2013; original draft, Writing &#x2013; review and editing.</p>
</sec>
<sec sec-type="COI-statement" id="s13">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="s14">
<title>Generative AI statement</title>
<p>The authors declare that no Generative AI was used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="s15">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<fn-group>
<fn fn-type="custom" custom-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1346700/overview">Sarmistha Saha</ext-link>, GLA University, India</p>
</fn>
<fn fn-type="custom" custom-type="reviewed-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1209845/overview">Minghui Li</ext-link>, Army Medical University, China</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3289990/overview">Pradeep Mankodi</ext-link>, Maharaja Sayajirao University of Baroda, India</p>
</fn>
</fn-group>
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