16 pages, 4 tables, 3 figures, Antimicrobial tolerance is a significant concern in the food industry, as it poses risks to food safety and public health. To overcome this challenge, synergistic combinations of antimicrobials have emerged as a potential solution. In this study, the combinations of two essential oil constituents (EOCs), namely carvacrol (CAR) and eugenol (EUG), with the quaternary ammonium compounds (QACs) benzalkonium chloride (BAC) and didecyldimethylammonium chloride (DDAC) were evaluated for their antimicrobial effects against Escherichia coli and Bacillus cereus, two common foodborne bacteria. The checkerboard assay was employed to determine the fractional inhibitory concentration index (FICI) and the fractional bactericidal concentration index (FBCI), indicating the presence of bactericidal, but not bacteriostatic, synergy in all QAC–EOC combinations. Bactericidal synergism was clearly supported by Bliss independence analysis. The bactericidal activity of the promising synergistic combinations was further validated by time–kill curves, achieving a >4-log10 reduction of initial bacterial load, which is significant compared to typical industry standards. The combinations containing DDAC showed the highest efficiency, resulting in the eradication of bacterial population in less than 2–4 h. These findings emphasize the importance of considering both bacteriostatic and bactericidal effects when evaluating antimicrobial combinations and the potential of EOC–QAC combinations for sanitization and disinfection in the food industry., This research was funded by Xunta de Galicia under grants IN606A-2020/028 and IN607B 2023/04, by MCIN/AEI/10.13039/501100011033 and “ERDF A way of making Europe” under grant PID2022-136817OB-I00, by FEDER funds through the Operational Programme Competitiveness Factors-COMPETE, and by national funds by FCT—Foundation for Science and Technology under research grants EXPL/MED-QUI/1156/2021, LA/P/0045/2020 (ALiCE), UIDB/00511/2020, UIDP/00511/2020 (LEPABE)., Peer reviewed

15 pages, 2 tables, 4 figures.-- Under a Creative Commons license, Antimicrobial heteroresistance refers to the presence of different subpopulations with heterogeneous antimicrobial responses within the same bacterial isolate, so they show reduced susceptibility compared with the main population. Though it is widely accepted that heteroresistance can play a crucial role in the outcome of antimicrobial treatments, predictive Antimicrobial Resistance (AMR) models accounting for bacterial heteroresistance are still scarce and need to be refined as the techniques to measure heteroresistance become standardised and consistent conclusions are drawn from data. In this work, we propose a multivariate Birth-Death (BD) model of bacterial heteroresistance and analyse its properties in detail. Stochasticity in the population dynamics is considered since heteroresistance is often characterised by low initial frequencies of the less susceptible subpopulations, those mediating AMR transmission and potentially leading to treatment failure. We also discuss the utility of the heteroresistance model for practical applications and calibration under realistic conditions, demonstrating that it is possible to infer the model parameters and heteroresistance distribution from time-kill data, i.e., by measuring total cell counts alone and without performing any heteroresistance test, We thank the grants PID2022-136817OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”, the grant IN607B 2023/04 by Xunta de Galicia, Spain and the grant 20213AT001 by CSIC, Spain, Peer reviewed

16 pages, 7 figures, 1 table, During adaptive laboratory evolution experiments, any unexpected interruption in data monitoring or control could lead to the loss of valuable experimental data and compromise the integrity of the entire experiment. Most homemade mini-bioreactors are built employing microcontrollers such as Arduino. Although affordable, these platforms lack the robustness of the programmable logic controller (PLC), which enhances the safety and robustness of the control process. Here, we describe the design and validation of a PLC-controlled morbidostat, an innovative automated continuous-culture mini-bioreactor specifically created to study the evolutionary pathways to drug resistance in microorganisms. This morbidostat includes several improvements, both at the hardware and software level, for better online monitoring and a more robust operation. The device was validated employing Escherichia coli, exploring its adaptive evolution in the presence of didecyldimethylammonium chloride (DDAC), a quaternary ammonium compound widely used for its antimicrobial properties. E. coli was subjected to increasing concentrations of DDAC over 3 days. Our results demonstrated a significant increase in DDAC susceptibility, with evolved populations exhibiting substantial changes in their growth after exposure, This research was funded by Xunta de Galicia (grants IN606A-2020/028 and IN607B 2021/11) and MCIN/AEI/10.13039/501100011033 “ERDF A way of making Europe” (grants PID2022-136817OB-I00 and DPI2014-54085-JIN), Peer reviewed

22 pages, 5 figures, This study details a biorefinery approach to valorize Dosidicus gigas squid pen waste. The process starts with the enzymatic deproteinization of squid pens, which prove effective with both Alcalase and Novozym, with the latter exhibiting a slightly higher efficiency to yield a material with 73% chitin content. Subsequent alkaline hydrolysis produces highly deacetylated chitosan (>90% degree of deacetylation), followed by controlled depolymerization to obtain polymers with molecular weights ranging from 50 to 251 kDa. Both native and depolymerized chitosan exhibit antimicrobial activity against Escherichia coli and Bacillus cereus, with B. cereus demonstrating greater resistance to chitosan compared to E. coli. The research also explores the bioconversion of deproteinization and deacetylation effluents. Deproteinization effluents prove superior in sustaining microbial growth, supporting comparable growth and lactic acid production for human probiotic strains (Lactobacillus plantarum and Leuconostoc mesenteroides) when substituting commercial peptones. Marine bacteria (Pseudomonas fluorescens and Phaeobacter sp.) show lower productivity. Integrating these processes into a biorefinery framework enables the conversion of 1 kg of dry squid pens into 350 g of chitosan, and facilitates the production of 937–949 g of lactic acid using human lactic acid bacteria cultures in media formulated with squid pen-derived effluents, glucose, yeast extract, and mineral salts. This integrated approach highlights the potential for maximizing resource utilization from squid pen waste, reducing environmental impact and generating high-value bioproducts., This research was funded by FCT/MCTES (PIDDAC): LEPABE, UIDB/00511/2020 (DOI: 10.54499/UIDB/00511/2020) and UIDP/00511/2020 (DOI: 10.54499/UIDP/00511/2020) and ALiCE, LA/P/0045/2020 (DOI: 10.54499/LA/P/0045/2020). Authors from IIM-CSIC are grateful to the EU Interreg Program (IBEROS+) (0072_IBEROS_MAIS_1_E, Interreg-POCTEP 2021–2027), GRC support program (ED431C 2021/49) and (GPC_IN607B 2024/010) from Xunta de Galicia, the project LIFE-REFISH (Project 101074323, LIFE21-ENV-ES-LIFE REFISH), and Grant PID2022-136817OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” for financial support. Marta Lima thanks the Portuguese Foundation for Science and Technology (FCT) for the financial support of her Ph.D. grant (2022.11196.BD)., Peer reviewed

11 pages, 6 figures, 4 tables, This work presents a mechanistic mathematical model describing the dynamics of microbial contamination in water during the washing of fresh produce. The model accounts for key processes, including microbial transfer from food product to water, dilution effects, and inactivation by chlorine-based antimicrobials under varying organic matter loads. These mechanisms reflect those previously identified and endorsed by the European Food Safety Authority (EFSA) as relevant for assessing microbial risks in wash water systems. To enable its application across diverse industrial settings, we propose a methodology for case-specific model adaptation. This involves conducting a targeted experiment designed using principles of Optimal Experimental Design (OED), allowing for the collection of data that are sufficiently informative to confidently estimate unknown model parameters. Industrial relevance: The proposed framework provides the food industry with a flexible and efficient tool for estimating unknown parameters essential for microbial risk assessment and for optimizing fresh produce washing processes, This work was funded by EFSA, Contract number OC/EFSA/ BIOCONTAM/2021/02 on “Microbiological hazards associated with the use of water in the post-harvest handling and processing operations of fresh and frozen fruits, vegetables and herbs (ffFVHs)” and the opinions expressed are those of the contractors only and do not represent the contracting authority’s (EFSA’s) official position.
We thank the grants PID2022-136817OB-I00 funded by MCIN/AEI/10.13039/501100011033/FEDER and the grant IN607B 2023/04 by Xunta de Galicia, Peer reviewed

10 pages, 6 figures, 1 table, Washing fresh produce is essential to remove soil and to inactivate microorganisms that may pose risks in products commonly consumed raw. However, operating continuous flume-tank systems is challenging because of variable produce loads and the spatiotemporal interplay between water quality and sanitiser chemistry.
This research addresses this challenge by developing a digital twin that optimally controls water and sanitiser additions during continuous flume tank operation. Its main component is a mechanistic model describing water quality dynamics, sanitiser decay, and microbial inactivation along the tank. This model is used offline to solve a multi-objective optimisation problem that balances water replenishment and sanitiser dosing while enforcing hygiene limits defined as a maximum allowable bacterial concentration at the tank outlet. The resulting Pareto front highlights how optimal solutions shift depending on whether water savings or sanitiser reductions are prioritised, and reveals the impractical volumes of water required when relying solely on water replenishment. For online use, the digital twins adjust the optimal solutions based on real-time measurements of incoming produce mass, ensuring the hygiene requirement under fluctuating loads. This work demonstrates how digital twins can enhance both resource efficiency and microbiological safety in industrial produce washing, We thank the grants PID2021-123654OB-C32, PID2022-136817OB-I00, PID2022-1417080B-I00, and PID2024-157718OB-C32, funded by MCIN/AEI/10.13039/501100011033/FEDER. Additionally, the authors are thankful for the financial support from AGROALNEXT program (MCIN and NextGenerationEU funds, PRTR–C17.I1) and Xunta de Galicia (IN607B 2023/04), Peer reviewed

19 pages, 6 figures, 1 table, Adaptive laboratory evolution (ALE) is a powerful tool for understanding and controlling the evolutionary trajectories of microorganisms. The scope of applications extends widely, including areas such as: biotechnology, synthetic biology, microbial ecology, and fundamental evolutionary research. In this work, we systematically explore the implementation and advantages of mini-bioreactors, defined as reactors with working volumes below 0.5 L, in ALE experiments. Mini-bioreactors offer substantial improvements over traditional large-scale reactors, including: reduced costs, enhanced parallelization capabilities, customizable configurations, and ease of automation. Through the utilization of illustrative case studies, which facilitate a comparative and critical evaluation of: batch, chemostat, turbidostat, and morbidostat operational modes, this review underscores the distinct capabilities of mini-bioreactors in enabling precise, dynamic control of evolutionary pressures. The novelty of this review lies in its comprehensive synthesis of recent advancements in mini-bioreactor technologies and operational strategies, particularly emphasizing innovations, such as: integrated automation, advanced sensors, and novel control algorithms adapted or specially designed for ALE. The ultimate objective is to provide both novices and experienced researchers with an updated, in-depth resource that addresses current technological limitations and future directions of mini-bioreactors in ALE, This work received funding from PID2022-136817OB-I00, AEI/10.13039/501100011033/FEDER, UE and Xunta de Galicia IN606A-2020/028 and IN607B 2021/11, Peer reviewed