Antimicrobial Activity of Chemical Hop (Humulus lupulus) Compounds: A Systematic Review and Meta-Analysis

Abstract

Humulus lupulus, commonly known as hop, is a climbing plant whose female cones impart beer’s characteristic bitterness and aroma and also serve as a preservative. In this study, we conducted a meta-analysis to investigate the antimicrobial activity of hop compounds and extracts against various microorganisms by statistically synthesizing minimum inhibitory concentration (MIC) values. From the 2553 articles retrieved from the comprehensive literature search, 18 provided data on MIC values for six hop compounds, and three extract types tested against 55 microbial strains’ MIC values corresponded to 24 and 48 h incubation periods with compounds or extracts. The results indicate that xanthohumol (a flavonoid) and lupulone (a bitter acid) exhibit potent antimicrobial activity against most tested microorganisms, particularly food spoilage bacteria [21.92 (95%CI 9.02–34.83), and 12.40 (95%CI 2.66–22.14) μg/mL, respectively, for 24 h of treatment]. Furthermore, hydroalcoholic extracts demonstrated greater efficacy compared to supercritical CO₂ (SFE) extracts, which showed limited antimicrobial effects against both probiotic and non-probiotic strains. These findings underscore the need for standardized, evidence-based protocols—including uniform microbial panels and consistent experimental procedures—to reliably evaluate the antimicrobial properties of hop-derived compounds and extracts. Taken together, our findings ultimately chart a path toward evidence based antimicrobial tests that could inform food-preservation strategies and inspire the development of plant-based antimicrobials.

1. Introduction

Humulus lupulus, commonly known as hop, is a dioecious climbing plant that belongs to the Cannabinaceae family, primarily cultivated for its critical role in the brewing industry [1]. The female flowers develop into cone-like structures called hops, which contain lupulin glands [1]. The key biochemical components of hops include primary metabolites, which support basic plant functions, and secondary metabolites that can influence ecological interactions of the plant [2]. The most notable secondary metabolites produced in lupulin glands include polyphenols (e.g., xanthohumol, isoxanthohumol, catechin), bitter acids (humulone, cohumulone, lupulone, colupulone), and essential oils (myrcene, caryophyllene) [3,4,5,6]. Bitter acids undergo isomerization during wort boiling to form iso-α acids, which are primarily responsible for beer’s bitterness [4]. Beyond brewing, hops are increasingly investigated for their pharmacological properties. Polyphenols, and particularly prenylated flavonoids, as well as the other hop constituents exhibit strong antioxidant and antimicrobial activities against Gram-positive and Gram-negative bacteria [3,5,7,8]. All these compounds contribute significantly to the flavor and aroma of beer, while they act as preservatives as well [9].

The antimicrobial activity of hops extends to bacteria, fungi, and parasites, primarily through prenylated flavonoids and bitter acids [1,10]; α- and β-acids have been shown to inhibit Gram-positive bacteria such as Staphylococcus and Streptococcus species [11] while xanthohumol and 6-prenylnaringenin exhibit antifungal and antiparasitic effects [11]. Furthermore, xanthohumol has demonstrated anticancer potential by targeting signaling pathways such as Akt and NF-κB, which are involved in cancer cell proliferation, survival, and metastasis [10,12]. Additional health benefits include anti-obesity effects through enhanced lipolysis and beta-oxidation, dermatological benefits such as skin protection and anti-aging, and hepatoprotective effects against liver diseases [13].

Antimicrobial assays—disk diffusion, broth and agar microdilution—remain the workhorses for profiling Humulus lupulus extracts (aqueous, ethanolic, supercritical CO₂) and purified phytochemicals such as xanthohumol and humulone against a broad spectrum of bacteria and fungi, including drug-resistant strains, as part of the global search for alternatives to conventional antibiotics [1,14,15,16]. Unfortunately, true cross-study comparison is restricted by methodological heterogeneity: disparate concentration units and dilution ranges, inoculum densities (10⁵–10⁶ CFU mL⁻¹), incubation regimes, media compositions, and visual or colorimetric MIC endpoints; plus the routine application of CLSI/EUCAST break-points optimized for hydrophilic drugs, which poorly predict the behavior of lipophilic hop polyphenols. When variable solubility, ad hoc strain selection, and inadequate quality-control reporting—deficiencies underscored in recent AST-workflow reviews [17,18]—are factored in, potency estimates lose reliability and, in turn, hinder evidence-based formulation in food, cosmetic, and pharmaceutical applications [19,20,21,22]. Our meta-analysis tackles these gaps by capturing granular assay metadata and apply subgroup analysis and meta-regression to quantify how extraction method, assay format, and microbial strain dictate observed efficacy, thereby generating the rigorous evidence base needed to advance hop-derived antimicrobials while sparing beneficial microbiota.

The objective of the present study is to systematically evaluate the antimicrobial efficacy of Humulus lupulus by synthesizing the available evidence through a robust, statistically rigorous approach. By conducting a meta-analysis of peer-reviewed studies, we aim to consolidate findings across diverse experimental contexts and identify key trends in the antimicrobial potency of hops. Specifically, we investigate the spectrum of activity against all bacterial strains tested to date, with a special emphasis on food spoilage microorganisms of significant relevance to public health and food industry sustainability. Furthermore, we examine the possibility of a potential probiotic sparing capacity of hop-derived compounds, a crucial consideration in preserving gut microbiota balance during antimicrobial treatment. Finally, we analyze differences in efficacy between Gram-positive and Gram-negative bacteria and assess how oxygen availability (aerobic versus anaerobic conditions) modulates antimicrobial performance. Accordingly, the objective of this study is to deliver the first systematic, evidence-based synthesis and quantitative appraisal of the antimicrobial, and functional properties of hop-derived phytoconstituents across food, cosmetic, and pharmaceutical applications [23,24,25], thereby providing a novel, integrated roadmap that can guide targeted formulation and process design in these industries.

2. Materials and Methods

2.1. Literature Search Strategy and Eligibility Criteria of Selected Studies

The literature search was conducted using the PubMed database to retrieve all potential research articles relevant to hop antimicrobial activity in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [26]. The literature search was conducted on 2/3/2024 using a combination of controlled vocabulary terms (e.g., MeSH) and free-text keywords, (i.e., hop or hops or “humulus lupulus”) and (antimicrobial or antifungal or antibacterial or chemoprevention or biofilm or antiparasitic or antiviral). This approach was taken to maximize sensitivity and ensure inclusion of recent or emerging terms not yet indexed in MeSH. To include all possible relevant articles the reference lists of the selected articles were also scrutinized. Three researchers (DK, EA, and PK) independently assessed the search results. Any discrepancies in the initial evaluations were resolved through discussion with two additional reviewers (PB and GB).

Eligible studies had to contain MIC values of hop compounds or extracts tested on microorganisms. Studies were excluded if they did not report MIC values or if the tested compounds and extracts were not derived from Humulus lupulus. Additionally, studies with incomplete or missing data were excluded, as their results could not be reliably evaluated. No language restrictions nor date (year) limit of publication were imposed to reduce the risk of publication bias related to gray literature [27]. Titles and abstracts of retrieved articles were screened, and relevant articles were assessed for inclusion/exclusion criteria. Risk of bias assessment could not be performed since the included datasets are not clinical outcomes.

2.2. Data Extraction

Data extraction from eligible studies was performed on a Microsoft Excel sheet. Search results were extracted independently by two researchers (DK and EA). Selected studies contained data on concentrations of Humulus lupulus extracts and compounds against different microorganisms. The extracted data included PubMed ID, first author’s last name, publication year, MIC values, along with their SD or SE values, bacteria species and strains, names compounds, types of extracts, along with experimental conditions such as incubation time and temperature, Gram classification (positive or negative), oxygen requirement (aerobic or anaerobic), and number of experimental replications. For studies reporting only the standard deviation (SD), the number of replicates was used to calculate the standard error of the mean (SEM) as follows: $SEM={\displaystyle \frac{SD}{\sqrt{n}}}$ Given that studies with no SD do have data that could shape the overall estimate of an effect size, they should not be excluded from a meta-analysis. Furakawa et al. [28] proposes that for a given meta-analysis a pooled SD could suffice to be imputed for the studies that do not have their own SD. In the present study we chose an even more conservative approach and if neither SD nor SEM was provided, the missing values were imputed using the highest SD reported among studies using the same compound and microorganism in order to downweight the missing studies [28]. Publication bias was assessed with Egger’s method [29].

2.3. Statistical Analysis

In the present meta-analysis, MIC values were used as effect size. The data were pooled using a random-effects meta-analysis [30] with inverse-variance weighting. MIC values and their 95% confidence intervals (CIs) were calculated for each compound across bacteria species, and incubation times. To quantify heterogeneity, I2 was used.

Stratification according to classification of hop compounds and extracts into sub-categories was performed to infer possible parameters of their bioactivity. Stratifications according to their effect on food preservation characteristics or health impact on humans (food spoilage/non-food spoilage or probiotic/non-probiotic) were also performed. To evaluate the impact of each individual study on the overall meta-analysis outcome, an influential analysis was conducted by sequentially excluding one study at a time and recalculating the statistical significance. Meta-analysis was performed with the statistical software Stata version 13.1, setting p-value for statistical significance less than or equal to 0.05 [31].

3. Results

3.1. Studies’ Selection and Characteristics

The literature search, following PRISMA guidelines, for antimicrobial activity of Humulus lupulus led to the retrieval of 2553 articles. After the application of eligibility criteria, we ended up with 18 articles that included 450 individual studies (Figure 1).

The included studies were investigating the antimicrobial activity of various hop compounds (Figure 2) that include flavonoids, bitter acids, and three types of extracts, i.e., supercritical fluid extracts (CO₂-based, SFE), hydroalcoholic, and hydroacetonic. From them, 122 report MIC values on flavonoids, 152 on bitter acids, 67 studies on CO₂-extracts, 79 on hydralcoholic extracts, and 28 on hydroacetonic extracts. Strains, which are used to measure antimicrobial activity against them, are 55. From the 450 studies, 174 of them were investigating antimicrobial effects after treatment for 24 h, while 276 studies reported results for the 48 h time point (

Table 1. Characteristics of the studies included in the meta-analysis.

Author	Year	Strain	Type of Compounds/Extracts	Number of Experiments	Time (h)	Temperature (°C)
Kramer et al. [32]	2015	Staphylococcus aureus/Listeria monocytogenes/Escherichia coli/Salmonella enterica	Xanthohumol/CO2-extract	4	48	37
Weber et al. [15]	2019	Propionibacterium acnes/Staphylococcus aureus	CO2-extract	3	24	37
Cermak et al. [33]	2017	Bacteroides fragilis/Clostridium perfringens/Clostridium difficile/	α-acids/β-acids/xanthohumol	4	48	37
Bogdanova et al. [34]	2018	Staphylococcus epidermidis/Staphylococcus capitis/Staphylococcus aureus/	Humulone/Lupulone/Xanthohumol	3	24	37
Larsona et al. [35]	1996	Listeria monocytogenes	CO2-extract	4	24	37
Klimek et al. [36]	2021	Staphylococcus aureus/Staphylococcus epidermidis/Streptococcus mutans/Streptococcus sanguinis/Propionibacterium acnes	Humulone/Lupulone/Xanthohumol	3	24/48	37
Bocquet et al. [37]	2019	Corynebacterium/Enterococcus faecalis/Enterococcus sp./Mycobacterium smegamtis/Staphylococcus aureus/Staphylococcus epidermidis/Staphylococcus lugdunensis/Staphylococcus warneri/Staphylococcus agalactiae/Staphylococcus dysgalactiae/Acinetobacter baumannii/Pseudomonas aeruginosa/Stenotrophomonas maltophilia/Candida albicans	Hydralcoholic-extract/Desmethylxanthohumol/Lupulone/Xanthohumol/Cohumulone/Humulone/Colupulone	3	24	37
Natarajana et al. [38]	2008	Bacillus subtilis/Bacillus megaterium/Streptococcus salivarius/Streptococcus saprophyticus	Humulone/Lupulone/Xanthohumol	2	24	37
Engels et al. [39]	2011	Bacillus subtilis/Bacillus cereus/Staphylococcus aureus/Listeria monocytogenes/Pediococcus acidilaactici/Lactococcus lactis/Pseudomonas fluorescens/Bacillus amyloliquefaciens/Staphylococcus warneri/Lactobacillus plantarum/Enterococcus faecalis/Campylobacter jejuni/Mucor plumbeus/Aspergillus niger/Penicillium spp.	Catechin	3	48	37
Rozalski et al. [40]	2013	Streptococcus aureus/Enterococcus faecalis	Hydralcoholic-extract/Xanthohumol/CO2-extract	4	24	37
Flesar et al. [41]	2010	Paenibacillus larvae	Organic-ethanolic extract/Organic-extract/Catechin	3	48	37
Bogdanova et al. [42]	2018	Staphylococcus aureus/Enterococcus faecalis/Staphylococcus haemolyticus/Candida albicans/Candida krusei/Candida tropicalis/Candida parapsilosis	Humulone/Lupulone/Xanthohumol/CO2-extract	4	48	25
Bhavya et al. [43]	2020	Staphylococcus aureus/Listeria monocytogenes/Bacillus subtilis	CO2-extract	4	48	25
Pilna et al. [44]	2015	Bifidobacterium dentium/Bifidobacterium longum/Lactobacillus salivarius/Streptococcus mutans/Streptococcus salivarius/Streptococcus sobrinus/Fusobacterium nucleatum/Candida albicans	Hydralcoholic-extract	3	48	37
Schmalreck et al. [45]	1974	Bacillus subtilis	Cohumulone/Isohumulone/Colupulone	3	24	37
Maia et al. [46]	2019	Saccharomyces cerevisiae/Lactobacillus fermentum/Leuconostoc mesenteroides	CO2 extract	2	48	37
Wei et al. [47]	2014	Mycobacterium smegmatis	Humulone	4	24	37
Kolenc et al. [48]	2022	Staphylococcus aureus/Lactobacillus acidophilus	Hydroacetonic extract	4	24	37

and Supplementary Table S1). The characteristics of the included studies reporting MIC values, incubation time, and experimental repetitions were taken into consideration for the meta-analysis.

3.2. Meta-Analysis of MIC Values of Classes of Hop Compounds and Extracts

A persistent challenge in evaluating the antimicrobial activity of hop-derived extracts lies in the considerable variability introduced by multiple factors. One major concern is determining which bacterial species and strains most accurately reflect the true antimicrobial potential, as susceptibility can vary widely even within a single species. At the same time, hop extracts contain a complex mixture of bioactive compounds, each present at different concentrations that can be significantly influenced by the genetic background [49], the extraction method and the solvent used. These variables complicate interpretation, as changes in extraction parameters may favor the presence of certain compounds while minimizing others.

Therefore, we chose to conduct a meta-analysis and include a broad panel of all bacterial strains ever tested for hop compounds or extracts. To better understand their specific contributions to antimicrobial activity, we stratified our meta-analysis according to the two major different classes of natural compounds, the flavonoids, that are polyphenols, and the bitter acids that are prenylated acylphloroglucinol derivatives. As shown in Figure 3A,

Table 2. Meta-analysis of MIC values of classes of hop compounds and extracts.

Compound	Time (h)	Strain	MIC	95% CI	Number of Studies	Publication Bias (p-Value)
Flavonoids	24	Staphylococcus epidermidis	1.37	0.12–2.61	3	N/A
		Staphylococcus aureus	13.61	6.41–20.81	15	0.272
		Bacillus subtilis	7.00	1.12–12.88	3	N/A
		Bacillus megaterium	10.00	9.20–10.80	3	N/A
		Streptococcus salivarius	23.33	10.27–36.40	3	N/A
		Streptococcus saprophyticus	2.33	1.03–3.64	3	N/A
		Streptococcus aureus	70.08	29.81–110.36	6	0.019
		Enterococcus faecalis	62.00	61.31–62.69	2	N/A
	48	Staphylococcus aureus	5.17	3.14–7.20	3	N/A
		Listeria monocytogenes	129.68	0.00–353.71	4	N/A
		Escherichia coli	200.0	199.43–200.57	3	N/A
		Salmonella enterica	200.0	199.43–200.57	3	N/A
		Bacteroides fragilis	39.43	27.76–51.06	7	0.001
		Clostridium perfringens	32.60	18.72–46.48	5	0.010
		Clostridium difficile	59.04	51.64–66.43	28	0.00
		Propionibacterium acnes	46.88	16.25–77.50	2	N/A
		Bacillus subtilis	1200.0	569.96–1830.0	3	N/A
		Pseudomonas fluroescens	1700.0	1699.2–1700.8	2	N/A
Bitter acids	24	Staphylococcus epidermidis	10.50	0.00–23.54	4	N/A
		Staphylococcus capitis	7.75	0.00–21.96	2	N/A
		Staphylococcus aureus	80.07	40.13–120.0	25	0.185
		Bacillus subtilis	90.25	0.00–255.52	12	0.587
		Bacillus megaterium	7.00	3.51–10.49	4	N/A
		Streptococcus salivarius	58.75	11.01–106.49	4	N/A
		Streptococcus saprophyticus	3.83	1.71–5.94	6	N/A
		Enterococcus faecalis	45.00	15.60–74.4	3	N/A
		Staphylococcus haemolyticus	15.50	0.00–43.92	2	N/A
	48	Bacteroides fragilis	512.90	287.91–737.80	14	0.001
		Clostridium perfringens	630.0	323.01–936.99	10	0.003
		Clostridium difficile	388.0	274.54–501.46	56	0.00
		Candida albicans	375.0	130.01–620.0	2	N/A
		Candida krusei	375.0	130.01–620.0	2	N/A
		Candida parapsilosis	750.0	260.01–1240.0	2	N/A
CO2-extract	24	Propionibacterium acnes	3.49	2.73–4.25	4	N/A
		Staphylococcus aureus	6.32	2.21–10.43	6	0.03
		Listeria monocytogenes	10.00	9.31–10.69	2	N/A
		Staphylococcus epidermidis	0.10	0.00–0.90	2	N/A
		Streptococcus aureus	1666.7	1013.4–2320.0	3	N/A
		Enterococcus faecalis	696.67	0.00–1974.0	3	N/A
	48	Staphylococcus aureus	46.43	0.00–99.10	7	0.135
		Listeria monocytogenes	37.19	0.00–90.93	7	0.224
		Escherichia coli	2604.2	1041.29–4167.1	6	0.022
		Salmonella enterica	2604.2	1041.29–4167.1	6	0.022
		Streptococcus mutans	0.39	0.00–1.19	2	N/A
		Streptococcus sanguinis	0.78	0.00–1.58	2	N/A
		Propionibacterium acnes	15.63	15.06–16.19	4	N/A
Hydralcoholic extract	24	Enterococcus faecalis	50.50	27.96–73.04	2	N/A
		Staphylococcus aureus	39.00	38.20–39.80	2	N/A
		Staphylococcus epidermidis	68.50	10.68–126.32	2	N/A
		Staphylococcus lugdunensis	390.50	0.00–850.11	2	N/A
		Staphylococcus warneri	332.0	0.00–906.27	2	N/A
		Streptococcus agalactiae	58.50	20.28–96,18	2	N/A
		Pseudomonas aeruginosa	625.0	624.20–625.80	2	N/A
		Candida albicans	273.33	0.00–624.26	3	N/A
		Streptococcus aureus	62.33	0.92–123,75	3	N/A
	48	Bifidobacteriumm dentium	213.33	160.44–266.22	6	0.001
		Bifidobacterium longum	96.00	67.95–124.05	6	0.001
		Lactobacillus salivarius	138.67	88.32–189.02	6	0.003
		Streptococcus mutans	106.67	80.22–133,11	6	0.001
		Streptococcus salivarius	34.67	22.08–47.25	6	0.003
		Streptococcus sobrinus	66.67	38.14–95,20	6	0.006
		Fusobacterium nucleatum	250.67	154.91–346.42	12	0.00
		Candida albicans	384.0	239.16–528.84	4	N/A
Hydroacetonic extract	24	Staphylococcus aureus	55.66	12.15–99.16	14	0.026
	48	Lactobacillus acidophilus	92.26	71.86–112.66	14	0.00

N/A: not applicable.

, and Supplementary Figure S1A,C, meta-analysis of MIC values of flavonoids and bitter acids, for 24 h of treatment, resulted in a variety of effectiveness depending on the species. However, in most of the cases, flavonoids exert better antimicrobial activity compared to bitter acids when tested in the same bacteria species and strains such as for Staphylococcus aureus (13.61 as opposed to 80.07 μg/mL), Staphylococcus epidermidis (1.37 versus 10.50 μg/mL), Streptococcus salivarius (23.33 versus 58.75 μg/mL) and Streptococcus saprophyticus (2.33 as opposed to 3.83 μg/mL) (Figure 3A). Although antimicrobial tests for 48 h of treatment were performed in different bacterial species, meta-analysis similarly showed elevated antimicrobial activity of flavonoids compared to bitter acids (Figure 3B, Supplementary Figure S1B,D).

In order to test the antimicrobial effectiveness of various types of hop extracts against microbial species, a meta-analysis was performed with the MIC values for each type of extract testing the effect on each microbial species. As shown in Figure 4A and Table 2, CO₂ (SFE) extracts showed a wide range of activity spanning from being the best antimicrobial agent against Staphylococcus aureus (MIC 6.32 μg/mL) to the worst antimicrobial agent against Streptococcus aureus (MIC 1667 μg/mL). A similar high divergence in antimicrobial activity was shown for CO₂ extracts for 48 h of treatment time and for different microbial species (Figure 4B and Table 2). Hydroalcoholic extracts exposed a more constant antimicrobial activity spanning from 39.0 (Staphylococcus aureus) to 625 μg/mL (Pseudomonas aeruginosa) for 24 h of treatment and from 34.67 (Streptococcus Salivarius) to 384 μg/mL (Candida albicans) for 48 h of treatment. Publication bias tests showed that it was more prominent for studies performed for 48 h of incubation (Table 2).

3.3. Stratification Meta-Analysis of MIC Values of Each Hop Compound

The flavonoids investigated in studies and included in the present meta-analysis are xanthohumol (XN) (chalcone) and catechin (flavanol), while bitter acids considered herein refer to humulone (alpha acid) and lupulone (beta acid). Flavonoids and bitter acids belong to different classes of natural compounds, each with distinct biosynthetic origins, structures, and chemical classifications [50,51].

Xanthohumol is a prenylated chalcone characterized by an open-chain flavonoid structure while catechin is a flavan-3-ol with a closed-ring structure and no prenylation. Similarly, humulone and lupulone share a phloroglucinol core but differ structurally: humulone contains an acyl side chain, while lupulone has three prenyl-type side chains, contributing to differences in bitterness and stability [52].

Thus, we stratified our meta-analysis according to each compound to understand the antimicrobial activity of each one, separately. As shown in Figure 5A and

Table 3. Meta-analysis of MIC values of individual hop compounds.

Class of Compound	Compound	Time (h)	Strain	MIC	95% CI	Number of Studies	Publication Bias (p-Value)
Flavonoids	Xanthohumol	24	Staphylococcus epidermidis	1.37	0.12–2.61	3	N/A
			Staphylococcus aureus	6.53	3.05–10.01	10	0.473
			Bacillus subtilis	7.00	1.12–12.88	3	N/A
			Bacillus megaterium	10.00	9.20–10.80	3	N/A
			Streptococcus salivarius	23.33	10.27–36.40	3	N/A
			Streptococcus saprophyticus	2.33	1.03–3.64	3	N/A
			Streptococcus aureus	70.08	29.81–110.36	6	0.019
			Enterococcus faecalis	62.00	61.31–62.96	2	N/A
		48	Bacteroides fragilis	39.43	27.80–51.06	7	0.001
			Clostridium perfringens	32.60	18.72–46.48	5	0.010
			Clostridium difficile	59.04	51.64–66.43	28	0.00
			Propionibacterium acnes	46.88	16.25–77.50	2	N/A
	Catechin	48	Bacillus subtilis	1200.0	569.96–1830.0	3	N/A
			Pseudomonas fluorescens	1700.0	1698.9–1701.1	2	N/A
Bitter acids	Humulone	24	Staphylococcus epidermidis	18.75	0.00–40.80	2	N/A
			Staphylococcus aureus	83.25	39.87–126.63	8	0.323
			Bacillus subtilis	5.01	0.33–9.69	4	N/A
			Streptococcus saprophyticus	5.31	1.20–9.42	3	N/A
			Enterococcus faecalis	60.00	59.31–60.69	2	N/A
	Cohumulone	24	Staphylococcus aureus	273.75	196.82–350.68	4	N/A
	α-acids (collectively)	48	Bacteroides fragilis	767.14	408.98–1125.3	7	0.006
			Clostridium perfringens	1062.0	808.46–1315.5	5	0.001
			Clostridium difficile	737.14	604.15–870.14	28	0.00
	Lupulone	24	Staphylococcus epidermidis	2.25	0.00–5.68	2	N/A
			Staphylococcus aureus	0.76	0.38–1.15	9	0.945
			Bacillus subtilis	2.33	1.03–3.64	3	N/A
			Bacillus megaterium	7.67	3.093–12.24	3	N/A
			Streptococcus salivarius	68.33	6.27–130.40	3	N/A
			Streptococcus saprophyticus	2.33	1.03–3.64	3	N/A
	β-acids (collectively)	48	Bacteroides fragilis	258.57	168.10–349.04	7	0.001
			Clostridium perfringens	198.00	161.123–234.877	5	0.00
			Clostridium difficile	38.39	39.40–130.10	28	0.00

N/A: not applicable.

, a meta-analysis was performed with MIC values from experiments with 24 h of treatment. XN exerted far better inhibition effectiveness against Staphylococcus aureus and Staphylococcus epidermidis (6.53 and 1.37 μg/mL) compared to the alpha acid humulone (83.25 and 18.75 μg/mL) but not compared to beta acid lupulone. Remarkably, against Bacillus Subtilis, Enterococcus faecalis and Streptococcus saprophyticus, XN, humulone and lupulone show similar effectiveness for 24 h incubation.

Importantly, the other flavonoid catechin, when tested for 48 h of incubation, revealed a very low antimicrobial activity against Bacillus subtilis and Pseudomonas fluorescens (1200 and 1700 μg/mL, respectively). Concerning bitter acids, lupulone seems to possess a significantly stronger antimicrobial agent compared to humulone (Figure 5B) for both 24 and 48 h of treatment. Publication bias assessment revealed that it was generally present in meta-analyses with studies assessing the MIC values for 48 h of incubation (Table 3).

3.4. Meta-Analysis of MIC Values of Hop Compounds and Extracts for Food Spoilage and Non-Food Spoilage Microorganisms

Given that food spoilage bacteria remain a major concern in food safety and shelf-life extension, and that hop has been used for centuries as a natural preservative in beer, it was intriguing to investigate whether hop compounds exhibit differential antimicrobial activity against food spoilage versus non-food spoilage bacteria. To this end, we stratified our meta-analysis according to the antimicrobial effects of hop-derived compounds and hop extracts against a diverse panel of food spoilage microorganisms, aiming to explore their potential selectivity and application beyond the brewing context [53,54,55].

Μeta-analysis of MIC values for classes of hop compounds (subgrouped according to each compound) and extracts, stratified for food spoilage and non-food spoilage bacteria (Supplementary Table S2), for 24 h of treatment, showed that XN exerted almost the same effect irrelevant of the food spoilage characteristics of the microorganisms (

Table 4. Meta-analysis of MIC values of hop compounds and extracts stratified according to food spoilage microorganisms.

Compound		Time (h)	Food Spoilage/Non-Food Spoilage	MIC	95% CI	Number of Studies	Publication Bias (p-Value)
Flavonoids		24	Food spoilage	22.81	11.54–34.08	33	0.550
			Non-food spoilage	21.68	0.00–47.71	6	0.00
		48	Food spoilage	242.25	9.61–474.88	26	0.00
			Non-food spoilage	263.28	130.45–396.11	49	0.190
	Xanthohumol	24	Food spoilage	21.92	9.02–34.83	28	0.632
			Non-food spoilage	21.68	0.00–47.71	6	0.00
		48	Food spoilage	23.46	8.76–38.15	7	0.060
			Non-food spoilage	54.32	48.10–60.54	40	0.643
	Catechin	48	Food spoilage	700.0	271.78–1128.2	7	0.265
			Non-food spoilage	1192.0	658.25–1725.8	9	0.038
Bitter acids		24	Food spoilage	66.09	3.23–128.59	51	0.333
			Non-food spoilage	20.32	6.64–34.0	11	0.090
		48	Food spoilage	573.64	277.54–869.74	11	0.410
			Non-food spoilage	427.38	332.38–522.01	77	0.00
	Humulone	24	Food spoilage	43.35	20.31–66.39	17	0.054
			Non-food spoilage	33.75	15.96–51.55	6	0.059
		48	Non-food spoilage	500.0	153.52–846.48	4	N/A
	Cohumulone	24	Food spoilage	273.75	196.82–350.68	4	N/A
	Lupulone	24	Food spoilage	12.40	2.66–22.14	21	0.157
			Non-food spoilage	4.20	0.00–9.97	5	0.349
		48	Non-food spoilage	666.67	340.01–993.33	3	N/A
CO2-extract		24	Food spoilage	421.91	0.95–842.87	12	0.296
			Non-food spoilage	260.35	0.00–625.64	12	0.283
		48	Food spoilage	1028.1	448.06–1608.1	31	0.252
			Non-food spoilage	257.81	10.61–505.01	8	0.044
Hydralcoholic extract		24	Food spoilage	52.65	28.39–76.86	8	0.573
			Non-food spoilage	290.94	163.21–418.68	18	0.349
		48	Food spoilage	86.67	64.58–108.75	24	0.00
			Non-food spoilage	238.35	180.99–295.71	29	0.00
Hydroacetonic extract		24	Food spoilage	55.66	12.15–99.16	14	0.026
		48	Food spoilage	92.26	71.86–112.66	14	0.00

N/A: not applicable.

and Figure 6A). Similarly, the α acid humulone showed comparable antimicrobial activities against food spoilage and non-food spoilage microorganism (43.35 and 33.75 μg/mL), while lupulone (beta-acid) showed significantly higher antimicrobial activity against non-food spoilage bacteria (4.20 compared to 12.40 μg/mL, respectively). Importantly, due to the small number of studies included, the last results should be considered with caution. For 48 h of treatment, xanthohumol showed enhanced antimicrobial activity against food spoilage compared to non-food spoilage microorganisms (23.46 and 54.32 μg/mL, respectively), as shown in Table 4 and Figure 6B.

Among the different types of extracts, hydroalcoholic extracts seemed to be more effective against food spoilage microorganisms for both 24 and 48 h of treatment. CO₂ extracts were less effective than hydroalcoholic extracts; however, 48 h of treatment resulted in higher antimicrobial effectiveness against non-food spoilage bacteria. Hydralcoholic extracts were more effective against food spoilage bacteria when tested for both 48 h (Table 4 and Figure 7). The MIC values for 48 h of treatment are expected to be lower than the MIC values for 24 h, because compounds have more time to exert their effect. However, it is important to note here that the tests for these different time points are performed with different microorganisms’ species which profoundly respond in a completely different way (Table 4 and Figure 7). Finally, publication bias was tested, and we observed that it was more frequent in meta-analyses of studies assessing the MIC for 48 h of incubation (Table 4).

3.5. Meta-Analysis of MIC Values of Hop Compounds and Extracts for Probiotic and Non-Probiotic Microorganisms

In light of current efforts to develop antimicrobials that are compatible with the human microbiome [56] and the long-standing use of hop compounds as natural antimicrobials, it is compelling to examine whether these compounds can selectively inhibit non-probiotic microorganisms while sparing probiotics. To this end, we conducted a meta-analysis of MIC data from the retrieved studies, to compare antimicrobial activity of hop-derived compounds against probiotic and non-probiotic strains. If such selectivity exists, these compounds could represent high-value functional agents, with potential to support human health by suppressing pathogens while preserving beneficial microbial communities.

To this end, the meta-analysis performed showed that antimicrobial activity of XN was stronger against probiotic compared to non-probiotic bacteria (Supplementary Table S2) when incubated for 24 h (8.49 as opposed to 24.75 μg/mL) (

Table 5. Meta-analysis of MIC values of hop compounds and extracts stratified according to probiotic or non-probiotic microorganisms.

Compound		Time (h)	Probiotic	MIC	95% CI	Number of Studies	Publication Bias (p-Value)
Flavonoids		24	No probiotic	25.21	12.67–37.74	33	0.009
			Probiotic	8.47	4.70–12.30	6	0.627
		48	No probiotic	213.28	110.83–315.72	62	0.691
			Probiotic	459.69	85.84–833.55	13	0.065
	Xanthohumol	24	No probiotic	24.75	10.17–39.33	28	0.015
			Probiotic	8.49	4.70–12.27	6	0.627
		48	No probiotic	51.52	44.42–56.11	40	0.021
			Probiotic	39.43	27.79–51.06	7	0.001
	Catechin	48	No probiotic	992.8	564.73–1420.9	10	0.323
			Probiotic	950.0	428.99–1471.0	6	0.949
Bitter acids		24	No probiotic	53.98	30.39–77.57	46	0.304
			Probiotic	69.44	0.00–209.31	16	0.564
		48	No probiotic	432.95	354.94–535.50	74	0.492
			Probiotic	512.86	287.91–737.8	14	0.001
	Humulone	24	No probiotic	50.81	27.03–74.58	18	0.198
			Probiotic	5.01	0.97–9.05	5	0.549
		48	No probiotic	500.0	153.52–846.48	4	N/A
	Cohumulone	24	No probiotic	273.75	196.82–350.68	3	N/A
	Lupulone	24	No probiotic	11.98	0.71–23.25	20	0.046
			Probiotic	4.93	2.71–7.15	6	0.071
		48	No probiotic	502.5	140.19–846.81	4	N/A
CO2-extract		24	No probiotic	326.46	14.29–638.63	22	0.206
			Probiotic	502.5	0.00–1477.6	2	N/A
		48	No probiotic	892.11	385.11–1399.1	38	0.108
Hydralcoholic extract		24	No probiotic	217.62	120.96–314.27	26	0.143
		48	No probiotic	180.11	124.26–235.97	35	0.00
			Probiotic	149.33	115.7–182.97	18	0.00
Hydroacetonic extract		24	No probiotic	55.66	12.15–99.16	14	0.026
		48	Probiotic	92.26	71.86–112.66	14	0.00

N/A: not applicable.

and Figure 8A). However, this difference was diminished when treatment occurred for 48 h (Table 5 and Figure 8B). Because there is a significant difference in the number of studies included in each meta-analysis, the last-mentioned results should be interpreted with caution (Table 5).

In addition, our meta-analysis revealed that hydroalcoholic extracts were more potent than CO₂ extracts in both 24 and 48 treatment time points (Figure 9). We should again strengthen the fact that experiments of compounds and extracts performed for different incubation time periods test different microorganisms and this could explain why MIC values in 48 h are not lower than MIC values in 24 h. Publication bias assessment revealed that it was more frequent in meta-analyses of studies assessing the MIC for 48 h of incubation (Table 5).

3.6. Meta-Analysis of MIC Values of Hop Compounds and Extracts Stratified According to Gram +/− and Oxygen-Requirement Microorganisms

Gram classification profoundly shapes intrinsic drug susceptibility: the thick, accessible peptidoglycan of Gram-positive cells contrasts with the lipopolysaccharide-rich outer membrane and efflux machinery that shield Gram-negative bacteria, creating distinct permeability barriers and resistance phenotypes [57,58,59,60]. Because hop prenylated flavonoids and bitter acids are relatively hydrophobic, their ability to traverse or destabilize these radically different envelope architectures is expected to diverge, making a Gram-based stratification essential for interpreting the true spectrum of activity. Accordingly, we conducted subgroup meta-analyses for Gram-positive and Gram-negative strains (Supplementary Table S2). As shown in Figure 10A and

Table 6. Meta-analysis of MIC values of hop compounds and extracts stratified according to Gram-positive or Gram-negative microorganisms.

Compound	Time (h)	Gram	MIC	95% CI	Number of Studies	Publication Bias (p-Value)
Flavonoids	24	Positive	22.64	12.42–32.85	39	0.667
	48	Positive	182.91	52.78–313.0	63	0.00
		Negative	427.6	70.30–784.9	10	0.840
Bitter acids	24	Positive	57.97	4.19–111.8	62	0.206
	48	Positive	432.95	333.4–532.5	74	0.492
		Negative	512.86	287.9–737.8	14	0.001
CO2-extract	24	Positive	341.13	73.5–608.8	24	0.365
	48	Positive	870.01	393.2–1347	39	0.360
Hydralcoholic extract	24	Positive	143.55	61.69–225.4	22	0.330
		Negative	625.0	624.4–625.6	4	N/A
	48	Positive	136.8	101.2–172.4	40	0.00
		Negative	270.8	174.3–367.3	13	0.00
Hydroacetonic extract	24	Positive	55.66	12.15–99.16	14	0.026
	48	Positive	92.26	71.86–112.7	14	0.00

N/A: not applicable.

, MIC values for Gram-positive bacteria are lower than those of Gram-negative suggesting that thicker peptidoglycan walls of Gram-positive are more permeable to hops compounds compared to the outer lipopolysaccharides membrane of Gram-negative. These results indicate that the hydrophobic prenylated flavonoids and bitter acids freely penetrate the porous peptidoglycan of Gram-positive bacteria, whereas the LPS outer membrane of Gram-negative species restricts their uptake, leading to higher MIC values in the latter group.

Oxygen phenotype intrinsically shapes a bacterium’s bioenergetics and redox balance: obligate aerobes derive ATP via ROS-producing oxidative phosphorylation, strict anaerobes rely on fermentation or non-oxygen electron acceptors, while facultative anaerobes can toggle between these pathways depending on environmental O₂ [61,62,63]. Prenylated flavonoids and bitter acids from hops collapse the proton-motive force and inhibit redox-sensitive dehydrogenases—targets that are most abundant in aerobic and facultative respiratory chains but largely absent in strict anaerobes [64,65,66,67]; so, their efficacy is expected to vary across these metabolic guilds. Therefore, stratifying our meta-analysis by aerobic, anaerobic, and facultative anaerobic groups (Supplementary Table S2) provides mechanistic context for any differential MIC patterns and clarifies where hop-derived compounds may be most therapeutically or industrially applicable. Accordingly, we carried out oxygen-based subgroup analyses (Supplementary Table S2). Our results (Figure 10B and

Table 7. Meta-analysis of MIC values of hop compounds and extracts stratified according to oxygen tolerance activity microorganisms.

Compound	Time (h)	Probiotic	MIC	95% CI	Number of Studies	Publication Bias (p-Value)
Flavonoids	24	Facultative anaerobic	23.94	12.20–35.68	36	0.006
		Aerobic	7	1.12–12.88	3	N/A
	48	Facultative anaerobic	287.2	48.54–525.88	16	0.807
		Aerobic	642.9	273.8–1012	13	0.059
		Anaerobic	59.23	45.99–58.46	43	0.749
Bitter acids	24	Facultative anaerobic	50.22	28.04–72.40	50	0.473
		Aerobic	90.25	0–255.5	12	0.587
	48	Facultative anaerobic	375	130.0–620.0	2	N/A
		Anaerobic	438.5	343.7–533.4	82	0.00
		Aerobic	627.5	214.3–1040	4	N/A
CO2-extract	24	Facultative anaerobic	408.7	98.99–718.3	20	0.272
		Anaerobic	3.49	2.73–4.25	4	N/A
	48	Facultative anaerobic	44.09	7.92–80.25	19	0.278
		Aerobic	2.19	1197–3173	15	0.022
		Anaerobic	62.5	0–162.2	5
Hydralcoholic-extract	24	Facultative anaerobic	190.0	94.481–285.4	23	0.196
		Aerobic	429.7	46.820–812.5	3	N/A
	48	Facultative anaerobic	142.3	89.950–194.7	29	0.00
		Anaerobic	202.7	147.354–257.9	24	0.00
Hydroacetonic-extract	24	Facultative anaerobic	55.66	12.15–99.16	14	0.026
	48	Facultative anaerobic	92.26	71.86–112.66	14	0.00

N/A: not applicable.

) reveal that hop compounds exhibit higher MIC values for aerobic bacteria compared to anaerobic or facultative anaerobic ones. Finally, publication bias was more prominent for studies performed for 48 h of incubation (Table 6 and Table 7). Taken together, the higher MICs against aerobic species suggest that hop compounds act most efficiently in low-oxygen or anaerobic niches—information that can guide their deployment in food packaging, gut-targeted formulations and products, or fermentation systems where anaerobic bacteria dominate. As natural, plant-based antimicrobials, hop compounds could meet the growing demand for clean-label solutions and may also support antibiotic use by reducing the needed dose and slowing resistance development.

4. Discussion

The evaluation of the antimicrobial potential of Humulus lupulus (hop) extracts and compounds has consistently highlighted significant variability, arising from differences in bacterial strains, extraction methods, experimental conditions, and the intrinsic diversity of phytoconstituents. The establishment of evidence-based practices, including standardized protocols for assessing antimicrobial activity, is critical for the scientific community to reliably compare, and interpret these findings. Without standardization, evaluating results across studies remains challenging, limiting the translation of hop-derived antimicrobial agents into clinical or commercial applications [56,68].

This systematic review and meta-analysis aimed to combine all available data to deliver a comprehensive, statistically rigorous synthesis of the antimicrobial activity of Humulus lupulus extracts and purified compounds, thereby informing future studies and practical applications. While hops have long been used for their preservative role in brewing, and their pharmacological potential has gained increasing attention, the methodologically diverse nature of existing studies has limited the development of a consolidated view of their antimicrobial efficacy. By integrating MIC data across 450 individual studies and 55 microbial strains, we contribute a much-needed evidence-based framework that enhances the reliability and reproducibility of antimicrobial findings related to hop-derived substances.

Our meta-analysis indicated substantial differences in the antimicrobial efficacy among hop-derived compounds. Specifically, we found pronounced variability in activity between chalcones such as xanthohumol and flavanols like catechin. Xanthohumol consistently showed potent antimicrobial effects, notably against Staphylococcus epidermidis (with MIC value 1.37 μg/mL) and Clostridium species (MIC value 32.6 μg/mL), with significantly lower MIC values compared to catechin, which exhibited minimal activity (MIC value 1200 μg/mL against Bacilus subtilis). Similarly, alpha acids (humulone) demonstrated markedly different antimicrobial profiles compared to beta acids (lupulone), with lupulone generally showing higher potency across multiple microbial species. These findings are in accordance with other reviews highlighting the broad-spectrum antimicrobial and biofilm-inhibiting properties of prenylated chalcones and bitter acids [1,10].

These compound-specific differences underscore the critical importance of chemical structure and functional groups in antimicrobial potency. For instance, the prenylated chalcone structure of xanthohumol, which facilitates cellular membrane penetration, differs substantially from the less effective non-prenylated flavan-3-ol structure of catechin [24,25]. Similarly, structural distinctions between alpha and beta acids—primarily in side-chain composition and prenylation—directly influence their respective antimicrobial activities. Additionally, we observed significant strain-specific variations in antimicrobial susceptibility, highlighting the complexity of microbial responses and reinforcing the need for careful strain selection when evaluating antimicrobial agents.

In addition, hydroalcoholic extracts exhibited more consistent antimicrobial performance than CO₂ extracts, which displayed highly variable outcomes depending on the tested microorganism. Because alpha and beta acids constitute more than 50% of a supercritical fluid-extracted hop extract, its antiproliferative effects are largely driven by bitter acids [36,51]. Given that beer, originally, is the hydroalcoholic solvent for dry hops, data coming from hydroalcoholic extracts are expected to be of more practicability. However, it is also quite a common practice for beer manufacturers to add condense, CO₂-based (SFE) extracts in bulk beer preparations [6] and [GmbH & Co. KG.] (from https://www.barthhaas.com/ (accessed on 30 May 2025). This variability in methodologies adds complexity and discrepancy in research and industrial tests and underscores the need for careful selection of extraction methods, solvents, and compound standardization—a critical issue raised in other meta-analyses on botanical antimicrobials [69].

An unexpected finding from our study was the variability in antimicrobial activity between the incubation periods of 24 and 48 h. Contrary to general expectations, many MIC values at 48 h were higher than at 24 h. This inconsistency primarily reflects the substantial variation in bacterial species and strains tested across these time points. Similar observations have been reported previously, suggesting differential microbial adaptive responses over extended exposure times [70]. This further emphasizes the urgent need for the scientific community to adopt a standardized panel of microbial strains and time points for evaluating MIC, thus enhancing comparability and reproducibility of antimicrobial studies.

One of the critical contributions of this work is the stratified meta-analysis that distinguishes between effects on food spoilage microorganisms, and probiotics. This functional stratification is of growing importance, especially in the context of microbiome-conscious antimicrobial development. For instance, xanthohumol showed promising selective action, exerting stronger effects on non-probiotic and food spoilage bacteria in several contexts, but also inhibiting probiotics at certain time points, underscoring the complexity of predicting microbial selectivity. Such diversifying behavior reinforces the need for integrated evaluations combining in vitro data with microbiome-sensitive in vivo testing, as proposed in diagnostics-focused meta-evaluations [68,70].

Our stratified analyses paint a straightforward picture of where hop compounds work best. They were consistently more effective against Gram-positive bacteria than Gram-negative ones, a pattern that fits with cell-wall architecture: the open, thick peptidoglycan of Gram-positives lets hydrophobic hop acids slip through, whereas Gram-negatives possess an outer lipopolysaccharide membrane that blocks many large, oily molecules [71]. We also saw lower MIC values in anaerobic and facultative anaerobic bacteria compared with strict aerobes. Because these low-oxygen microbes rely on redox-sensitive enzymes and a fragile proton-motive force to make energy, hop prenylated flavonoids and bitter acids—known to disrupt both—exert a markedly stronger inhibitory effect on them [65]. Taken together, the data show that hop compounds favor organisms with permeable walls and oxygen-sensitive metabolism, offering a predictable spectrum of activity.

From an application standpoint, the potency patterns uncovered in our meta-analysis align with several formulation routes that are already moving from bench to pilot scale: (a) food protection [72,73], (b) cosmetic antimicrobials [15], (c) therapeutic adjuvants [38,74]. Together, these proof-of-concept studies outline a concrete industrial and clinical roadmap: hop β-acids and prenyl-chalcones can be selected from a larger pool of candidates for (i) controlled-release films and coatings for “clean-label” foods, (ii) cosmetic formulations targeting acne and body odor, and (iii) oral or topical antibiotic-potentiating adjuncts. Embedding such compound-specific formulation scenarios into future trials will accelerate the translation of our evidence-based efficacy estimates into real-world antimicrobial products.

However, our study is not without limitations. Primarily, the absence of complete methodological details in several original studies introduced uncertainties in data interpretation. For instance, variations in experimental protocols such as compound handling, dilution procedures, storage conditions, extraction methodologies, quantitative and qualitative extract composition, bacterial inoculum density, incubation conditions, and solvent composition can significantly influence MIC values. This scarcity of detailed information rendered it impossible to perform meaningful stratification based on these parameters. Additionally, reliance on imputed standard deviations in certain cases could potentially introduce biases into the meta-analysis outcomes. Our analysis also faced methodological challenges due to the inclusion of heterogeneous data, emerging from heterogeneity in experimental protocols, encompassing various hop compounds, extracts, bacterial species, and incubation durations. Despite these difficulties, our rigorous statistical methods—including stratified meta-analyses and sensitivity analyses—allowed us to manage this complexity and derive reliable conclusions. Our findings affirm that hop compounds exhibit reproducible trends in antimicrobial activity, but these can only be reliably interpreted within a unified, evidence-based framework that adequately accounts for methodological heterogeneity. Importantly, the current findings advocate for a more systematic approach to future antimicrobial testing of hop-derived agents. Furthermore, meta-analysis, as demonstrated here and in studies like [50,68,69,75,76] is a powerful tool to extract meaningful trends from heterogeneous datasets, and should be routinely employed in future investigations of natural product pharmacology.

5. Conclusions

This meta-analysis delivers the first quantitatively robust map of hop-derived antimicrobials, demonstrating that specific β-acids (lupulone) and prenylated chalcones (xanthohumol) can match—or surpass—benchmark preservatives against key food-spoilage and pathogenic bacteria, while hydro-alcoholic extracts provide the most reliable performance profile. By synthesizing 450 studies for 55 microbial strains, we expose how compound class, extraction solvent, and incubation time, jointly shape potency; in doing so, we supply reproducible evidence that the field has so far lacked. At the same time, our findings reveal how fragmented methodologies, non-standard microbial panels, and inconsistent reporting still add confusion to the true boundaries of efficacy. Addressing these gaps is now the chief barrier to commercial or clinical uptake: without harmonized protocols, neither regulators nor product formulators can compare results with confidence. Future work should therefore progress to factorial in vitro and in vivo studies, pre-clinical and early-phase clinical trials that test pharmacotechnical combinations (nano- or hydrogel-encapsulated combinations) of lupulone, xanthohumol, and sub-inhibitory doses of standard antibiotics or food preservatives, simultaneously mapping dose response, release kinetics, and microbiome impact to optimize synergistic formulations for food, cosmetic, and therapeutic use. In parallel, the scientific community of the microbiology field (food, cosmetics, pharmaceuticals, industry) must adopt unified breakpoints, solvent controls, and strain panels to ensure that emerging data abide with the evidence framework we provide. Only through this twin track (methodological standardization and application-focused experimentation) can the clear promise of hop compounds be translated into safe, effective preservatives, cosmetic antimicrobials, and antibiotic-potentiating adjuncts that are ready for real-world deployment.