UsingGalleria mellonellato study pathogen dissemination and anti-infective surface coatings

Using Galleria mellonella to study pathogen dissemination and anti-infective surface coatings | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Using Galleria mellonella to study pathogen dissemination and anti-infective surface coatings Evgenia Maslova , Ciaram Staber , View ORCID Profile Ronan R McCarthy doi: https://doi.org/10.1101/2024.06.11.598455 Evgenia Maslova 1 Division of Biosciences, Department of Life Sciences, Centre of Inflammation Research and Translational Medicine, College of Health and Life Sciences, Brunel University London , Uxbridge, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ciaram Staber 1 Division of Biosciences, Department of Life Sciences, Centre of Inflammation Research and Translational Medicine, College of Health and Life Sciences, Brunel University London , Uxbridge, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ronan R McCarthy 1 Division of Biosciences, Department of Life Sciences, Centre of Inflammation Research and Translational Medicine, College of Health and Life Sciences, Brunel University London , Uxbridge, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ronan R McCarthy For correspondence: ronan.mccarthy{at}brunel.ac.uk Abstract Full Text Info/History Metrics Preview PDF Abstract Hospital associated infections and localised hospital outbreaks are a major challenge for infection control teams (ICTs) in hospitals around the world. Advances in artificial intelligence and infection modelling have enabled ICT teams to better predict and trace infection spread. However, it is notoriously difficult to replicate bacterial dissemination or validate prediction models in a laboratory setting due to a lack of effective in vivo models. In this work, we sought to develop Galleria mellonella as a model organism to replicate the dissemination of pathogens in a hospital intensive care unit (ICU). By combining this model organism with 3D printed models of a real hospital ICU, we are able to demonstrate that larvae do disseminate the multidrug resistant pathogen Acinetobacter baumannii within this ICU model and that it is possible to use this model to identify infection hotspots. Importantly, this model can also be used for intervention strategy testing as we also show that bacterial dissemination can be significantly mitigated by the introduction of antimicrobial wall surface coatings. This model provides a robust platform for the testing of antimicrobial surface coatings as well as the study of genetic determinants with a role in pathogen dissemination. Introduction Controlling the spread of nosocomial pathogens within the hospital-built environment is a major challenge for infection control teams (ICT), particularly as many of these nosocomial pathogens are multidrug resistant. Acinetobacter baumannii is a Gram-negative opportunistic pathogen primarily associated with causing nosocomial infections. A. baumannii is recognised as the World Health Organisations number one priority pathogen due to its capacity for causing localised hospital outbreaks, its ability to survive on hospital surfaces for prolonged periods and its recalcitrance to antibiotic therapy ( Doughty et al ., 2023 , Green et al ., 2022 , J.D. Hunter, 2012 , Ibrahim et al ., 2017 , Fernández-Billón et al .,2023 , Pachori, Gothalwal ,& Gandhi’s, 2019 , Chen et al . 2022 ). Developments in sampling, sequencing and tracking technologies have made it possible to visualise and analyse pathogen spread in hospital settings in near real-time ( Haverkate et al ., 2015 , Nguen et al., 2020, King et al ., 2021 , Doughty et al ., 2023 ). Modelling is also gaining an increasing importance in uncovering how these pathogens disseminate. Several in situ simulations have been developed in order to visualise and predict pathogen dissemination in hospital wards ( Gibbs et al ., 2018 , Kotay et al ., 2017 ). However, the majority of simulation models such as agent-based model (ABM), system dynamics model (SD) and hybrid simulation models do not facilitate prevention strategy testing nor do they typically facilitate the study of different strains of the same species (Nguen et al ., 2020). The further experimental validation of these simulation models is often not feasible as there is a lack of affordable in vivo dissemination models available. In this study, we propose a bacterial dissemination model utilising Galleria mellonella as the surrogate vector for pathogen spread. G. mellonella is a robust model organism that has gained popularity in recent decades. This model organism has been used for a wide range of assays including virulence assays (bacterial and fungal), immunotoxicity testing (concerning the adaptive immune system), drug toxicity assays, testing the effects of ultraviolet radiation, probiotics, and bacteriophage treatment efficacy ( Cunha et al ., 2023 , Stempinski, Smith and Casadevall 2022 , Erbas et al ., 2023 , Demirtürk, Uçkan, and Mert, 2023 , Sabockyte et al ., 2023 , Filippov et al ., 2022 , Maslova et al ., 2023 ). G. mellonella are affordable, have low ethical considerations associated with their use and have low maintenance and handling requirements which could facilitate faster early-stage pathogen dissemination and prevention strategy testing. Here, we demonstrate the capacity of a G. mellonella larvae-based model to be used as a tool to study bacterial dissemination and to evaluate the efficacy of antimicrobial surface coatings in vivo . Results G. mellonella act as vectors to disseminate bacteria throughout a 3D printed ICU model Hospitals are potent reservoirs for several opportunistic multidrug resistant bacterial pathogens. Due to the nature of the healthcare environment, pathogens can disseminate via a multitude of routes and agents within the hospital setting, with humans being one of the primary vectors for infection spread ( Webb et al ., 2005 , Hassoun-Kheir et al ., 2020 ). Here, we proposed an ICU ward model utilising the G. mellonella as a surrogate for humans as vectors of pathogen dissemination. To add additional clinical relevance to our model, we designed a replica hospital ward based off publicly available schematics of Brigham and Women’s Hospital ICU (MA). The model included 11 patient rooms, a hallway and a central nurses station ( Figure 1A ). The 3D printed model was sterilized using an IMS solution and tested to confirm that the larvae can move freely around the model ICU (Video 1). We then tested whether the larvae could spread bacteria around the hospital by placing the model ICU on a bed of LB agar and subsequently introducing a single site of bacterial colonisation in Room 13 which is the central nurses station. This location was chosen due to the previous reports highlighting non-treatment areas such as doctor and nurse stations as important environmental reservoirs for bacteria ( Dumford et al ., 2009 , Bures et al ., 2000 , Tajeddin et al ., 2016 ). We chose to inoculate the ICU with a sample of A. baumannii AB5075. A. baumannii is a highly prevalent nosocomial pathogen commonly associated with ICU outbreaks around the world ( Wieland et al ., 2018 ). A single larva was then added to the model and allowed to move freely through the bays of the model for 16-18 hours. Based on visual observation of the agar bed underneath the ICU model, it was clear that bacteria had been spread throughout every room in the ICU ( Figure 1C ). Download figure Open in new tab Figure 1. The experimental design and layout of the hospital ICU ward. (A) The outline of the hospital ICU model. (B) The experimental set-up with the 3D printed ICU model placed upon a bed of LB agar. A piece of agar seeded with A. baumannii AB5075 can be seen in Room 13 (Central Nurses Station). (C) The bacterial dissemination by a singular G. mellonella larva can be seen as growth on an LB agar after 16-18h incubation A. baumannii AB5075. To develop the model further, we replaced the LB agar bed (which facilitates bacterial growth) with Whatmann paper and included 11 larvae in the model (one for each of the ICU rooms with the exception of the nurses station and the hall) ( Figure 2A ). To enable the quantification of bacterial dissemination, after a 24-hour incubation period, the walls of each room were swabbed and the colony forming units (CFUs) from each enumerated ( Figure 2B ). The nurses station (Room 13) reproducibly returned the highest CFU values as expected, as it was where the initial starting inoculum was located. Rooms 1-5, 7 and 12 had higher CFU levels than the rest of the rooms, which was expected as Room 12 is the “hallway” of the ICU model and would therefore have the highest visit count. Rooms 1-5 are the first rooms the larva would encounter once exiting Room 13 which also explains the high CFU counts in these rooms. Rooms 6-7 and 8-11 had the lowest number of bacteria recovered. This data demonstrates that the model can be used to study bacterial dissemination throughout a replica ICU and to identify potential hotspots for bacterial contamination. Download figure Open in new tab Figure 2. Uncoated ICU model set up with 11 larvae (A) and the average A. baumannii AB5075 CFU values obtained from each room (B) . This data represents the average CFUs obtained from 6 biological replicates after 24h incubation with average shown with SD. Ordinary one-way ANOVA with Tukey correction was performed, p value < 0.0001. Surface coating decreases bacterial bioburden on the model surfaces Once the bacterial load distribution within the ICU model was confirmed, we next sought to explore the capacity of the model to be used to evaluate antimicrobial surface coatings. Antimicrobial surface coatings are commonly used to limit microbial surface contamination and represent a potential strategy to limit the spread of pathogens within a hospital. We developed a PVA based paint solution supplemented with gentamicin as the antimicrobial agent ( Menetrez et al ., 2008 , Fulmer et al ,, 2011 , Ren et al ., 2022 ). Gentamicin was chosen for its ability to maintain potency even after being exposed to the high temperatures needed to dissolve the polymers. In the model with the gentamicin loaded surface coating, less bacteria were recovered in every single room as compared to the models with no coating, with statistically significant reductions seen in rooms 1, 2, 5, 8, 10, 12 and 13 ( Figure 3 , 4 ). Overall, this demonstrates the capacity of this model to effectively determine the efficacy of antimicrobial surface coatings in vivo . Download figure Open in new tab Figure 3. The bacterial spread by G. mellonella in the non-coated and gentamicin coated ICU models. The bacterial spread of A. baumannii with uncoated (A) and gentamicin (B) coated model respectively. The color coding corresponds to the highest (red), the medium high (yellow) and the low (green) bacterial densities. Room 13 was the infection start site and has the highest CFU in both ICUs. Download figure Open in new tab Figure 4. The CFU counts recovered from each room of the gentamicin coated and non-coated ICUs models. Gentamicin treated rooms exhibited a consistent reduction in CFUs with the exception of rooms 9 and 11. Rooms 3,4,6,7,9,11 exhibited no significant decrease in CFUs. This experiment has 6 biological repeats. Unpaired student t-test not significant p value was >0.05, * p value <0.05, ** p value < 0.005. Discussion Amidst the multidrug resistance crisis, understanding the dissemination of nosocomial pathogens through the hospital-built environment is crucial. Here, we developed a bacterial dissemination model utilizing 3D printing and G. mellonella as the pathogen dissemination vector. This model was tested with A. baumannii , a notorious nosocomial bacterial pathogen with a remarkable capacity to survive on surfaces for prolonged periods. It was shown that the larvae could traverse the entire hospital ICU ward model within a 16-18h window, spreading bacteria to the entire ICU in the process ( Figure 1C ). This can be viewed as a pathogen starting in one bay then possibly being spread to others via an individual commuting between bays in the ward while not adhering to appropriate safety and infection control protocols. Having shown the proof-of-principle that one larva was able to spread bacteria throughout the ICU, the bacterial spread was quantified in a multi-vector experiment. This would allow us to determine what areas were at a higher risk. The amount of larva used per Petri dish was increased to match the number of outer rooms being 11. As expected, the highest number of CFUs were recovered from the center room which is labelled Room 13 (Nurses station) ( Figure 2B ). Rooms closest to the entrance of Room 13 typically had higher CFU numbers. These being Rooms 1-5 and 12 with 12 being the central corridor connecting all rooms. Rooms that were further from that entrance like 9, 10 and 11 showed lower CFUs. This trend shows that the CFU recovered generally goes down from room to room with increasing distance from the start site. While in this study we used insects as surrogates for human pathogen spread, several studies have also demonstrated the relevance of insects such as cockroaches and ants as vectors/reservoirs for multidrug resistant bacteria in the hospital environment highlighting their role in nosocomial infection spread ( Fowler et al ., 1993 , Do Nascimento et al ., 2020 , Abdolmaleki et al ., 2020 , Menasria et al ., 2014 , Hassan et al ., 2021 ). With confirmation of the bacterial spread by G. mellonella throughout the model, further testing was done to determine if this model could be used to test potential antimicrobial agents. The PVA base polymer coating was chosen due to its low costs and low toxicity (DeMerlis and Schomeker, 2003). PVA is already well established within the pharmaceutical and medical industry for a wide array of applications. Across all experiments the results showed that a gentamicin coating was able to reduce the CFUs recovered ( Figure 3 , 4 ). Clearly, the use of antibiotics directly within a surface coating in everyday use is not realistic as it would contribute to further pressures for antibiotic resistance. However, as a proof of principle it validates the capacity of this model to be used as an in vivo tool for testing the efficacy of antimicrobial surface coatings. Such a model has the potential to accelerate the development of these technologies and add further relevance to in silico models that already exist in the field. The experimental set-up is highly versatile, for example bespoke 3D models can be designed to give representative insights for a specific hospital, the initial inoculation site can be altered, the number of larvae/ vectors can be modified. Equally the options for surface coatings can be modified to address a specific research question, testing for example different doses or formulations. Equally, different pathogens, polymicrobial communities, surface biofilms can all be tested in the model. The is also the possibility that the surface of the model can be washed and the assay can be repeated to determine the durability and leeching of any surface coating. The model can also be run at scale, facilitating the generation of large volumes of data that can be used to train artificial intelligence applications or to test in silico dissemination models. A key consideration however is that the movement of the larvae is more random and less directed as compared to the movements of hospital staff on a ward, however the same limitation is likely to apply to any animal used in a hospital dissemination model study. The model also has the potential to be used to study the genetic determinants of infection dissemination as different strains can be used to inoculate the model and their relative capacity for dissemination and persistence can be determined. Equally, if specific genes have been hypothesized as being linked to transmissibility or built environment persistence, it will be possible to use this model to gain in vivo insights about the consequences of mutating or overexpressing these genes. In conclusion, this study demonstrates G. mellonella ICU model can be used to study pathogen dissemination and the capacity of surface coatings to limit this dissemination. Materials and methods Bacteria strains and growing conditions A. baumannii AB5075 was grown overnight at 37°C in 5ml of LB broth at 180 rpm for 16-18h. To obtain the lawn, 100 µl of the AB5075 overnight culture was put onto a nonselective LB agar plate and spread evenly across the surface using a sterile swab or inoculation loop. Then grown at 37°C for 16-18h. Incubation of the single larva experiment set up with the patch of bacteria lawn was for 16-18h at 37°C, and 24h for the set up with 11 larvae. Once samples were collected, serially diluted, and plated they were incubated in the static incubator for 16-18 h then counts were taken. Animal acquisition and preparation G. mellonella were sourced from LiveFood UK Ltd. (Somerset, United Kingdom). The larvae were stored at 4°C in wood shavings upon arrival until use. During the selection process, the larvae were checked to ensure there was no signs of melanization along its body as it is a sign of an infection or trauma in G. mellonella ( Pereira et al ., 2018 ). Once selected, the larvae were sterilized by rolling the larva in a shallow pool of 70% IMS in a sterile Petri dish. The larva was then dried off by putting it on a sterile piece of blue paper towel roll. The larvae were then moved to a sterile Petri dish and incubated at 4°C until needed. Due to the storage at 4°C, the larvae remain immobile until they warm up to the room temperature which facilitates easier sterilization and handling of the larvae during the experiment set up. 3D printed ICU model The schematic ICU model was made using a resin (PVA) and a 3D printer (Elegoo Mars 2 Pro). It was modelled off of an intensive care ward of Brigham and Womans Hospital, MA, USA. The model was stored in a dry cool place when not in use and was sterilised by soaking it in 70% industrial methylated spirits (IMS) for a minimum of 90 seconds prior to use. It was then moved to sterile Petri dish and allowed to air dry in a laminar flow hood. Once dry, it was placed on top of the LB agar media for the single larva experimental set up. For the 11 larvae set up, no agar was introduced into the Petri dish and layers of foil were used to elevate the ICU until it met the lid of the Petri dish when closed, preventing larvae from climbing over the walls. Whatmann filter paper was then used to separate the foil layers and the ICU model. ICU model bacterial dissemination assay set-up with a single larva 10 ml of lysogeny (LB) agar was poured into a sterile Petri dish. Once dried, the sterile ICU model was placed on top of the agar. The Petri dish was then covered, and the lid gently pressed to implant the ICU model onto the agar. A 50µl droplet of A. baumannii AB5075 overnight culture adjusted to OD 600 = 1 was then pipetted into the central Nurses Station referred to as Room 13. A single larva was then placed into same room as the bacteria. The set-up was incubated at 37°C for 16-18 h. After the incubation period, the larva was euthanized by placing it at -20°C. The ICU model was removed from the agar and the bacterial spread left by the larva in the Petri dish was assessed. ICU model bacterial dissemination set up used to obtain bacterial load data from the walls of the ICU A 1 cm 2 patch was cut out of an LB agar plate that was seeded with a lawn of A. baumannii AB5075 on it. The patch was then placed into the Nurses station of the ICU replica. Sterilised larvae were then added to each outer room of the ICU. Tape was used to secure the lid to the plate so that there was no gap between the walls of the ICU effectively making the lid of the Petri dish, the ceilings of the ward. The Petri dish was then be incubated for 24h at 37ºC. ICU model walls CFU sample collection and evaluation At 24 hours all larvae were moved to -20°C and euthanized. The ICU model was then moved to a new sterile Petri dish using sterile tweezers. A sterile PBS-soaked swab was then used to sample each room, moving to swab across all walls. The swab’s tip was broken off into an Eppendorf tube with 500 µl PBS and vortexed. This was repeated for each room including the Nurses Stations (central room, Room 13) and the corridor. The samples were then serially diluted to 10 -5 in PBS and plated onto LB agar supplemented with 50 µg/ml kanamycin, to limit any background growth. The plates were incubated for 16-18h. Post incubation, individual colonies were counted and used to calculate the colony forming units (CFUs) of each room. Surface coating mixture composition and preparation The surface coating solution was made using the composition proposed by Marcelo et al . (2022) . The polyvinyl alcohol (PVA):polyvinylpyrrolidone(PVP) polymer solution was made by dissolving 2000 mg of PVA and 500 mg of PVP in 15 mL of distilled water. The mixture was then incubated in the 80°C water bath, occasionally being vortexed until the solution went from cloudy to transparent. Using this solution as a base coating solution, the total volume would be used to make % w/v treatment solution mixtures. Gentamicin was chosen for its ability to maintain potency even after enduring the high temperature needed to dissolve the polymers. Gentamicin 16 mg/ml was used as the positive control as this above the EUCAST breakpoint for A. baumannii . Coating the ICU surface After undergoing sterilisation and drying the ICU model would be coated with the desired mixtures containing the active ingredient. This was done by saturating a cotton swab in 1 ml of the solution. The swab was then used to coat the outer walls of each room 1-12. The same swab was remoistened and used to coat the inner and outer wall of the central room. This was repeated until virtually all the 1 ml of solution was used up whilst re-saturating the swab every 3-4 rooms. Only one swab was used to coat each ICU model. The same procedure would then be followed as described in the infection spread set up section mentioned above, but with the coated ICUs. Statistical analysis For analysis of the total CFU recovery of the ICU models the one-way ANOVA with Tukey correction test was used. Analysis of the antibiotic coating solution efficacy to reduce bacterial proliferation was done using unpaired student t-test. Funding information RRMC and EM are supported by a National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) studentship award NC/V001582/1. RRMC is supported by a Biotechnology and Biological Sciences Research Council New Investigator Award BB/V007823/1 and the Academy of Medical Sciences/the Wellcome Trust/ the Government Department of Business, Energy and Industrial Strategy/the British Heart Foundation/Diabetes UK Springboard Award [SBF006\1040] and MRC MR/Y001354/1. Conflict of Interest Disclosure The authors have no conflicts of interest to declare. Data Availability All data including the 3D printed model of the ICU are available from the corresponding author. References ↵ Abdolmaleki , Z. , Mashak , Z. and Safarpoor Dehkordi , F. ( 2020 ) ‘Molecular and Virulence Characteristics of Methicillin-Resistant Staphylococcus aureus Bacteria Recovered From Hospital Cockroaches’ , Jundishapur journal of microbiology , 12 ( 12 ), pp. 1 - 6 Available at : doi: 10.5812/jjm.98564 . OpenUrl CrossRef ↵ Bures , S. , Fishbain , J.T. , Uyehara , C.F.T. , Parker , J.M. and Berg , B.W. ( 2000 ) ‘Computer keyboards and faucet handles as reservoirs of nosocomial pathogens in the intensive care unit’ , American Journal of Infection Control , 28 ( 6 ), pp. 465 - 471 Available at : doi: 10.1067/mic.2000.107267 . OpenUrl CrossRef PubMed Web of Science ↵ Chen , Y. , Chen , X. , Liang , Z. , Fan , S. , Gao , X. , Jia , H. , Li , B. , Shi , L. , Zhai , A. , & Wu , C. ( 2022 ). Epidemiology and prediction of multidrug-resistant bacteria based on hospital level . Journal of global antimicrobial resistance , 29 , 155 – 162 . doi: 10.1016/j.jgar.2022.03.003 OpenUrl CrossRef ↵ Cunha , F. , Burne , A. , Casaro , S. , Brown , M. B. , Bisinotto , R. S. , & Galvao , K. N. ( 2023 ). Establishing Galleria mellonella as an invertebrate model for the emerging multi-host pathogen Helcococcus ovis . Virulence , 14 ( 1 ), 2186377 . doi: 10.1080/21505594.2023.2186377 OpenUrl CrossRef ↵ Demirtürk , Z. , Uçkan , F. , & Mert , S. ( 2023 ). Interactions of alumina and polystyrene nanoparticles with the innate immune system of Galleria mellonella . Drug and chemical toxicology , 1 – 13 . Advance online publication. doi: 10.1080/01480545.2023.2217484 OpenUrl CrossRef DeMerlis , C.C. and Schoneker , D.R. ( 2003 ) ‘Review of the oral toxicity of polyvinyl alcohol (PVA)’ , Food and Chemical Toxicology , 41 ( 3 ), pp. 319 – 326 Available at : doi: 10.1016/S0278-6915(02)00258-2 . OpenUrl CrossRef PubMed ↵ Do Nascimento , L.E. , Amaral , R.R. , Ferreira , R.M.D.A. , Trindade , D.V.S. , Do Nascimento , R.E. , Da Costa , T.S. and Souto , R.N.P. ( 2020 ) ‘Ants (Hymenoptera: Formicidae) as Potential Mechanical Vectors of Pathogenic Bacteria in a Public Hospital in the Eastern Amazon, Brazil’ , Journal of medical entomology, 57(5) , pp. 1619 – 1626 Available at : doi: 10.1093/jme/tjaa062 . OpenUrl CrossRef ↵ Doughty , E.L. , Liu , H. , Moran , R.A. , Hua , X. , Ba , X. , Guo , F. , Chen , X. , Zhang , L. , Holmes , M. , van Schaik , W. , McNally , A. and Yu , Y. ( 2023 ) ‘ Endemicity and diversification of carbapenem-resistant Acinetobacter baumannii in an intensive care unit’ , The Lancet regional health.Western Pacific , 37 , pp. 100780 Available at : doi: 10.1016/j.lanwpc.2023.100780 . OpenUrl CrossRef ↵ Dumford , D.M. , MD , Nerandzic M.M.BS , Eckstein B.C.BS and Donskey , C.J. , MD ( 2009 ) ‘ What is on that keyboard? Detecting hidden environmental reservoirs of Clostridium difficile during an outbreak associated with North American pulsed-field gel electrophoresis type 1 strains’ , American Journal of Infection Control , 37 ( 1 ), pp. 15 – 19 Available at : doi: 10.1016/j.ajic.2008.07.009 . OpenUrl CrossRef PubMed Web of Science ↵ Duman Erbas , E. , Gwokyalya , R. , Altuntas , H. , & Kutrup , B. ( 2023 ). Screening the immunotoxicity of different food preservative agents on the model organism Galleria mellonella L. (Lepidoptera: Pyralidae) larvae . Drug and chemical toxicology , 46 ( 4 ), 757 – 767 . doi: 10.1080/01480545.2022.2091589 OpenUrl CrossRef ↵ Fernández-Billón , M. , Llambías-Cabot , A. E. , Jordana-Lluch , E. , Oliver , A. , & Macià , M. D. ( 2023 ). Mechanisms of antibiotic resistance in Pseudomonas aeruginosa biofilms . Biofilm , 5 , 100129 . doi: 10.1016/j.bioflm.2023.100129 OpenUrl CrossRef ↵ Filippov , A. A. , Su , W. , Sergueev , K. V. , Kevorkian , R. T. , Snesrud , E. C. , Srijan , A. , He , Y. , Fouts , D. E. , Lurchachaiwong , W. , McGann , P. T. , Ellison , D. W. , Swierczewski , B. E. , & Nikolich , M. P. ( 2022 ). Design of a Bacteriophage Cocktail Active against Shigella Species and Testing of Its Therapeutic Potential in Galleria mellonella . Antibiotics (Basel, Switzerland) , 11 ( 11 ), 1659 . doi: 10.3390/antibiotics11111659 OpenUrl CrossRef ↵ Fowler , H.G. , Bueno , O.C. , Sadatsune , T. et al. Ants As Potential Vectors of Pathogens in Hospitals in the State of Sao Paulo, Brazil . Int J Trop Insect Sci 14 , 367 – 370 ( 1993 ). doi: 10.1017/S1742758400014879 OpenUrl CrossRef ↵ Fulmer , P.A. and Wynne , J.H. ( 2011 ) ‘ Development of broad-spectrum antimicrobial latex paint surfaces employing active amphiphilic compounds’ , ACS applied materials & interfaces , 3 ( 8 ), pp. 2878 Available at : doi: 10.1021/am2005465 . OpenUrl CrossRef PubMed ↵ Gibbs , K. , DeMaria , S. , McKinsey , S. , Fede , A. , Harrington , A. , Hutchison , D. , Torchen , C. , Levine , A. and Goldberg , A. ( 2018 ) ‘ A Novel In Situ Simulation Intervention Used to Mitigate an Outbreak of Methicillin-Resistant Staphylococcus aureus in a Neonatal Intensive Care Unit’ , The Journal of pediatrics , 194 , pp. 22 - 27 .e5 Available at : doi: 10.1016/j.jpeds.2017.10.040 . OpenUrl CrossRef ↵ Green , E.R. , Fakhoury , J.N. , Monteith , A.J. , Pi , H. , Giedroc , D.P. and Skaar , E.P. ( 2022 ) ‘ Bacterial hydrophilins promote pathogen desiccation tolerance’ , Cell host & microbe , 30 ( 7 ), pp. 975 - 987 .e7 Available at : doi: 10.1016/j.chom.2022.03.019 . OpenUrl CrossRef ↵ Hassan , B. , Ijaz , M. , Khan , A. et al. A role for arthropods as vectors of multidrug-resistant Enterobacterales in surgical site infections from South Asia . Nat Microbiol 6 , 1259 – 1270 ( 2021 ). doi: 10.1038/s41564-021-00965-1 . OpenUrl CrossRef ↵ Hassoun-Kheir , N. , Stabholz , Y. , Kreft , J. , de la Cruz , R. , Romalde , J.L. , Nesme , J. , Sørensen , S.J. , Smets , B.F. , Graham , D. and Paul , M. ( 2020 ) ‘ Comparison of antibiotic-resistant bacteria and antibiotic resistance genes abundance in hospital and community wastewater: A systematic review’ , Science of The Total Environment , 743 , pp. 140804 Available at : doi: 10.1016/j.scitotenv.2020.140804 . OpenUrl CrossRef ↵ Haverkate , M.R. , Bootsma , M.C.J. , Weiner , S. , Blom , D. , Lin , M.Y. , Lolans , K. , Moore , N.M. , Lyles , R.D. , Weinstein , R.A. , Bonten , M.J.M. and Hayden , M.K. ( 2015 ) ‘ Modeling spread of KPC-producing bacteria in long-term acute care hospitals in the Chicago region, USA’ , Infection control and hospital epidemiology , 36 ( 10 ), pp. 1148 – 1154 Available at : doi: 10.1017/ice.2015.163 . OpenUrl CrossRef ↵ Hunter J. D. ( 2012 ). Ventilator associated pneumonia . BMJ (Clinical research ed .), 344 , e3325 . doi: 10.1136/bmj.e3325 OpenUrl FREE Full Text ↵ Ibrahim , S. , Al-Saryi , N. , Al-Kadmy , I.M.S. and Aziz , S.N. ( 2021 ) ‘ Multidrug-resistant Acinetobacter baumannii as an emerging concern in hospitals’ , Molecular biology reports , 48 ( 10 ), pp. 6987 – 6998 Available at : doi: 10.1007/s11033-021-06690-6 . OpenUrl CrossRef PubMed ↵ King , M. , Wilson , A.M. , Weir , M.H. , López-García , M. , Proctor , J. , Hiwar , W. , Khan , A. , Fletcher , L.A. , Sleigh , P.A. , Clifton , I. , Dancer , S.J. , Wilcox , M. , Reynolds , K.A. and Noakes , C.J. ( 2022 ) ‘Modeling fomite-mediated SARS-CoV-2 exposure through personal protective equipment doffing in a hospital environment’ , Indoor air , 32 ( 1 ), pp. e12938 - n /a Available at : doi: 10.1111/ina.12938 . OpenUrl CrossRef PubMed ↵ Kotay , S. , Chai , W. , Guilford , W. , Barry , K. and Mathers , A.J. ( 2017 ) ‘ Spread from the Sink to the Patient: In Situ Study Using Green Fluorescent Protein (GFP)-Expressing Escherichia coli To Model Bacterial Dispersion from Hand-Washing Sink-Trap Reservoirs’ , Applied and Environmental Microbiology , 83 ( 8 ), pp. E03327 Available at : doi: 10.1128/AEM.03327-16 . OpenUrl Abstract / FREE Full Text ↵ Marcelo , G. A. , Galhano , J. , Duarte , M. P. , Kurutos , A. , Capelo-Martínez , J. L. , Lodeiro , C. , & Oliveira , E. ( 2022 ). Functional Cyanine-Based PVA:PVP Polymers as Antimicrobial Tools toward Food and Health-Care Bacterial Infections . Macromolecular bioscience , 22 ( 12 ), e2200244 . doi: 10.1002/mabi.202200244 OpenUrl CrossRef ↵ Maslova , E. , Osman , S. and McCarthy , R.R. ( 2023 ) ‘ Using the Galleria mellonella burn wound and infection model to identify and characterize potential wound probiotics’ , Microbiology (Society for General Microbiology) , 169 ( 6 ) Available at : doi: 10.1099/mic.0.001350 . OpenUrl CrossRef ↵ Menasria , T. , Moussa , F. , El-Hamza , S. , Tine , S. , Megri , R. and Chenchouni , H. ( 2014 ) ‘ Bacterial load of German cockroach (Blattella germanica) found in hospital environment’ , Pathogens and global health , 108 ( 3 ), pp. 141 – 147 Available at : doi: 10.1179/2047773214Y.0000000136 . OpenUrl CrossRef PubMed ↵ Menetrez , M.Y. , Foarde , K.K. , Webber , T.D. , Dean , T.R. and Betancourt , D.A. ( 2007 ) ‘ Testing antimicrobial cleaner efficacy on gypsum wallboard contaminated with Stachybotrys chartarum’ , Environmental science and pollution research international , 14 ( 7 ), pp. 523 – 528 Available at : doi: 10.1065/espr2007.03.397 . OpenUrl CrossRef PubMed Nguyen , L.K.N. , Megiddo , I. and Howick , S. ( 2020 ) ‘ Simulation models for transmission of health care–associated infection: A systematic review’ , American Journal of Infection Control , 48 ( 7 ), pp. 810 – 821 Available at : doi: 10.1016/j.ajic.2019.11.005 . OpenUrl CrossRef ↵ Pachori , P. , Gothalwal , R. , & Gandhi , P. ( 2019 ). Emergence of antibiotic resistance Pseudomonas aeruginosa in intensive care unit; a critical review . Genes & diseases , 6 ( 2 ), 109 – 119 . doi: 10.1016/j.gendis.2019.04.001 OpenUrl CrossRef ↵ Pereira , T.C. , de Barros , P.P. , Fugisaki , L.R.d.O. , Rossoni , R.D. , Ribeiro , F.d.C. , de Menezes , R.T. , Junqueira , J.C. and Scorzoni , L. ( 2018 ) ‘ Recent Advances in the Use of Galleria mellonella Model to Study Immune Responses against Human Pathogens’ , Journal of fungi (Basel) , 4 ( 4 ), pp. 128 Available at : doi: 10.3390/jof4040128 . OpenUrl CrossRef ↵ Ren , Y. , Cai , J. , Cheung , H. , Shao , H. , Au , K. , Chow , T. , Wen , W. , Ling , L. and Chen , S. ( 2022 ) ‘ Controlling microbial activity on walls by a photocatalytic nanocomposite paint: A field study’ , American Journal of Infection Control , 50 ( 4 ), pp. 427 – 434 Available at : doi: 10.1016/j.ajic.2021.09.005 . OpenUrl CrossRef ↵ Sabockyte , A. , McAllister , S. , Coates , C. J. , & Lim , J. ( 2023 ). Effect of acute ultraviolet radiation on Galleria mellonella health and immunity . Journal of invertebrate pathology , 198 , 107899 . doi: 10.1016/j.jip.2023.107899 OpenUrl CrossRef ↵ Stempinski , P. R. , Smith , D. F. Q. , & Casadevall , A. ( 2022 ). Cryptococcus neoformans Virulence Assay Using a Galleria mellonella Larvae Model System . Bio-protocol , 12 ( 15 ), e4480 . doi: 10.21769/BioProtoc.4480 OpenUrl CrossRef ↵ Tajeddin , E. , Rashidan , M. , Razaghi , M. , Javadi , S.S.S. , Sherafat , S.J. , Alebouyeh , M. , Sarbazi , M.R. , Mansouri , N. and Zali , M.R. ( 2016 ) ‘ The role of the intensive care unit environment and health-care workers in the transmission of bacteria associated with hospital acquired infections’ , Journal of Infection and Public Health , 9 ( 1 ), pp. 13 – 23 Available at : doi: 10.1016/j.jiph.2015.05.010 . OpenUrl CrossRef PubMed ↵ Webb , G.F. , Erika M.C. D’Agata , Magal P. , Ruan , S. and Falkow , S. ( 2005 ) ‘ A Model of Antibiotic-Resistant Bacterial Epidemics in Hospitals’ , Proceedings of the National Academy of Sciences -PNAS , 102 ( 37 ), pp. 13343 – 13348 Available at : doi: 10.1073/pnas.0504053102 . OpenUrl Abstract / FREE Full Text ↵ Wieland , K. , Chhatwal , P. and Vonberg , R. ( 2018 ) ‘ Nosocomial outbreaks caused by Acinetobacter baumannii and Pseudomonas aeruginosa: Results of a systematic review’ , American Journal of Infection Control , 46 ( 6 ), pp. 643 – 648 Available at : doi: 10.1016/j.ajic.2017.12.014 . OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted June 11, 2024. Download PDF Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Using Galleria mellonella to study pathogen dissemination and anti-infective surface coatings Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Using Galleria mellonella to study pathogen dissemination and anti-infective surface coatings Evgenia Maslova , Ciaram Staber , Ronan R McCarthy bioRxiv 2024.06.11.598455; doi: https://doi.org/10.1101/2024.06.11.598455 Share This Article: Copy Citation Tools Using Galleria mellonella to study pathogen dissemination and anti-infective surface coatings Evgenia Maslova , Ciaram Staber , Ronan R McCarthy bioRxiv 2024.06.11.598455; doi: https://doi.org/10.1101/2024.06.11.598455 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Microbiology Subject Areas All Articles Animal Behavior and Cognition (7644) Biochemistry (17726) Bioengineering (13916) Bioinformatics (42033) Biophysics (21486) Cancer Biology (18635) Cell Biology (25549) Clinical Trials (138) Developmental Biology (13397) Ecology (19940) Epidemiology (2067) Evolutionary Biology (24361) Genetics (15620) Genomics (22541) Immunology (17763) Microbiology (40468) Molecular Biology (17207) Neuroscience (88739) Paleontology (667) Pathology (2842) Pharmacology and Toxicology (4834) Physiology (7659) Plant Biology (15175) Scientific Communication and Education (2047) Synthetic Biology (4304) Systems Biology (9834) Zoology (2272)