Bioimaging with fluorescent nucleic-acid aptamers for the specific detection and quantification of Pseudomonas aeruginosa alone and in heterogeneous bacterial populations

Bioimaging with fluorescent nucleic-acid aptamers for the specific detection and quantification of Pseudomonas aeruginosa alone and in heterogeneous bacterial populations | 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 Bioimaging with fluorescent nucleic-acid aptamers for the specific detection and quantification of Pseudomonas aeruginosa alone and in heterogeneous bacterial populations Chaimae Mezouarhi , View ORCID Profile Romain Vauchelles , Basma Abdallah , View ORCID Profile Janel Régine , Mouna Ouadghiri , View ORCID Profile Hassan Ait Benhassou , View ORCID Profile Pierre Fechter , View ORCID Profile Laurence Choulier doi: https://doi.org/10.1101/2025.02.07.636672 Chaimae Mezouarhi 1 UMR7021 Laboratory of Bioimaging and Pathologies, CNRS University of Strasbourg Illkirch , France 2 UMR7242 Laboratory of Biotechnology and Cell Signaling, CNRS University of Strasbourg Illkirch , France 3 Medical Biotechnology Laboratory, Medical and Pharmacy School, Mohammed V University , Rabat, Morocco 4 Prevention and Therapeutics Center, MAScIR, Mohammed VI Polytechnic University Ben Guerir , Morocco Find this author on Google Scholar Find this author on PubMed Search for this author on this site Romain Vauchelles 1 UMR7021 Laboratory of Bioimaging and Pathologies, CNRS University of Strasbourg Illkirch , France Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Romain Vauchelles Basma Abdallah 1 UMR7021 Laboratory of Bioimaging and Pathologies, CNRS University of Strasbourg Illkirch , France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Janel Régine 2 UMR7242 Laboratory of Biotechnology and Cell Signaling, CNRS University of Strasbourg Illkirch , France Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Janel Régine Mouna Ouadghiri 3 Medical Biotechnology Laboratory, Medical and Pharmacy School, Mohammed V University , Rabat, Morocco Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hassan Ait Benhassou 4 Prevention and Therapeutics Center, MAScIR, Mohammed VI Polytechnic University Ben Guerir , Morocco Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Hassan Ait Benhassou Pierre Fechter 2 UMR7242 Laboratory of Biotechnology and Cell Signaling, CNRS University of Strasbourg Illkirch , France Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Pierre Fechter Laurence Choulier 1 UMR7021 Laboratory of Bioimaging and Pathologies, CNRS University of Strasbourg Illkirch , France Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Laurence Choulier For correspondence: laurence.choulier{at}unistra.fr Abstract Full Text Info/History Metrics Supplementary material Preview PDF ABSTRACT The rising prevalence of bacterial infections, antibiotic resistance, and emerging pathogens underscores the urgent need for innovative diagnostic approaches. Aptamers, short nucleic acid sequences with high specificity and affinity for their targets, are promising candidates for diagnostic applications due to their ability to detect a wide range of pathogens. In this study, we present a fluorescent aptamer-based bioimaging approach for detecting Pseudomonas aeruginosa , a multidrug-resistant pathogen of significant clinical concern. Conjugated with fluorescent dye, the detection efficacy of the F23 aptamer was evaluated on 15 different Gram-negative and Gram-positive bacteria, including fixed and lived cells, as well as homogeneous and heterogeneous population. To quantify microscopy images, we developed an automated, open-access identification software using ImageJ. Its high sensitivity provides a robust platform for accurately quantifying bacteria labeled with aptamers and potentially other fluorescent ligands. For instance, it successfully detected 1122 P. aeruginosa cells labeled with aptamer F23 out of a total of 1123 P. aeruginosa cells in a single image. With almost 200,000 analyzed bacteria and an exceptionally clear signal-to-noise ratio, we demonstrated that the F23 aptamer effectively detects various reference and clinical strains of Pseudomonas aeruginosa , while failing to detect Gram-positive Staphylococcus aureus, Staphylococcus haemolyticus, Staphylococcus epidermidis and Corynebacterium striatum , as well as Gram-negative Klebsiella pneumonia, Acinetobacter baumannii , and Escherichia coli . The F23 aptamer is therefore a promising tool to distinguish Pseudomonas aeruginosa from different strains of the skin microbiota. However, our quantitative method also revealed partial labeling to other bacterial cells, highlighting the issue of refining aptamer selection to improve selectivity. 1. INTRODUCTION The urgent need for improved pathogen surveillance is driven by the growing global population, the increasing prevalence of bacterial infections, the emergence of new pathogens and antibiotic resistance. Accurate and rapid diagnosis methods are therefore becoming increasingly critical ( Bergkessel et al., 2023 ; Rudd et al., 2020 ). Conventional bacterial diagnosis relies on the culture of bacteria from body samples and the formation of colonies. While highly sensitive, capable of detecting as few as 10 1 −10 3 colony forming units per milliliter (CFU/mL), this method is slow, often requiring over 24 hours before staining and observation. Furthermore, it can be imprecise, and error-prone due to sample collection conditions and the specific growth requirements of certain bacteria ( Deusenbery et al., 2021 ). Fluorescence in situ hybridization (FISH) offers an alternative method to identify pathogenic bacteria that bypasses the need for culture. This technique requires fluorescently labeled probes designed to hybridize with complementary sequences of the target organism’s genetic material. When selecting probes for FISH, factors such as specificity, sensitivity and ease of tissue penetration must be considered. Traditional DNA-based FISH often requires permeabilization steps to facilitate probe entry into bacterial cells, which can be time-consuming and may potentially damage samples ( Batani et al., 2019 ; Gu et al., 2022 ; Moter and Göbel, 2000 ). Polymerase chain reaction (PCR) is another powerful biotechnological tool for identifying pathogens that are difficult to culture or require long incubation periods ( Yamamoto, 2002 ). Other diagnostic approaches, such as antibody-based biochemical assays and biosensors are also raising interest. These methods often demand specialized equipment, skilled operators, and can be expensive, limiting their accessibility. It is therefore essential to develop alternative diagnosis tools and methods that are simple, cost-effective, rapid, and sensitive ( Lin et al., 2023 ). Imaging technologies have the potential to significantly enhance bacterial detection by greatly improving both sensitivity and specificity, while enabling more accurate identification and real-time localization of infections. Advanced techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), can be integrated with molecular markers specifically designed to target bacterial components. These molecular probes bind to unique bacterial structures, such as cell walls or metabolic products ensuring precise visualization and differentiation from host cells. The combination of these imaging techniques with bacterial-specific markers allows for more precise monitoring of infection progression and treatment response ( Hameed et al., 2018 ). Moreover, imaging approaches facilitate multiplexed imaging to simultaneously detect multiple bacterial species or biomarkers in a single scan. This capability is particularly beneficial in clinical settings involving complex or polymicrobial infections, where interactions between different bacterial strains and host tissues impact disease progression. Multiplexed imaging provides a comprehensive overview of the infection landscape, delivering critical information for tailored therapeutic interventions and advancing precision medicine in the treatment of bacterial infections ( Zhang et al., 2023 ). Infections caused by Pseudomonas aeruginosa ( P. aeruginosa ) are of particular concern due to several critical factors. This multidrug-resistant opportunistic Gram-negative pathogen exhibits intrinsic resistance to many antibiotics and can rapidly acquire additional resistance through mutations and horizontal gene transfer, further challenging treatment options. Its extensive arsenal of virulence factors, including exotoxins, proteases, and the ability to form biofilms, enhances its capacity to cause severe and persistent infections while evading both antibiotics and the host immune response ( Botelho et al., 2019 ; Qin et al., 2022 ). Taking advantage of their weakened defenses, P. aeruginosa primarily targets immunocompromised individuals, such as cystic fibrosis patients, burn victims, chronic lung diseases sufferers, and hospitalized patients with invasive devices. These infections often lead to severe clinical outcomes, including pneumonia, bloodstream, urinary tract and surgical site complications. Furthermore, the pathogen’s ubiquitous presence in various environments, such as soil, water and moist surfaces in healthcare settings, facilitates the colonization of medical equipment and healthcare personnel, thereby raising the risk of nosocomial infections ( Jangra et al., 2022 ; Tuon et al., 2022 ). These characteristics highlight the urgent need for stringent infection control measures, and the development of advanced diagnostic approaches to mitigate the impact of P. aeruginosa infections. Nucleic acid aptamers are innovative tools for detection. These short single-stranded DNA or RNA molecules display high affinity and specificity for a wide range of targets, for example small molecules, proteins and whole cells, such as bacteria ( Song et al., 2012 ). This versatility opens up numerous applications in diverse fields including medicine, environmental monitoring, and biotechnology ( Zhou and Rossi, 2017 ). Aptamers also offer several advantages over traditional antibodies, such as ease of chemical synthesis, modification, as well as enhanced stability under diverse conditions, including fluctuations in temperature and pH. Aptamers’ affinity for their targets, generally in the micromolar to low picomolar range, is comparable and sometimes exceeds the performance of monoclonal antibodies ( Jenison et al., 1994 ). In recent years, the use of aptamers as antibacterial agents has gained significant attention due to their potential to fight bacterial infections. They can be engineered to selectively target and bind to bacterial cell surface components, such as adhesins, toxins, or essential enzymes involved in bacterial survival or virulence, offering a potent strategy to address the growing challenge of antibiotic resistance. Aptamers specificity allow them to selectively inhibit the growth or function of pathogenic bacteria without affecting non-targeted cells or tissues ( Afrasiabi et al., 2020 ; Wang et al., 2018 ). In clinical diagnostics, aptamers can bind to specific bacterial surface proteins or unique bacterial markers, triggering detectable signals that correlate with the presence and concentration of targeted bacteria. This combination of specificity and sensitivity make aptamers particularly valuable for detecting pathogenic bacteria in diverse clinical samples, such as blood, urine, or sputum, thereby enhancing diagnostic precision and enabling timely treatment interventions ( Guan and Zhang, 2020 ). Aptamer-based assays for bacterial toxins detection have gained significant attention. Examples include Aptamer-Linked Immobilized Sorbent Assay (ALISA) kits ( Taneja et al., 2020 ), aptamer-based biosensors ( Léguillier et al., 2024 ), aptamer-based Lateral Flow Assays (LFAs), Enzyme-Linked Aptamer-Sorbent Assays (ELASA) ( Rasoulinejad and Gargari, 2016 ). A key advantage of ELASA systems is regenerability, allowing for repeated use, enhancing the assay’s sustainability and cost-effectiveness. In contrast, antibodies often lack this regenerability, making them less suitable for long-term and cost-effective applications in diagnostics and research settings ( Gopinath and Kumar, 2013 ; Li et al., 2020 ). Fluorescence imaging strategies based on nucleic acid aptamers hold particular promise to detect bacteria that are difficult to culture, improving diagnostic accuracy, enabling early diagnosis and facilitating effective monitoring of bacterial infections. Aptamer-based fluorescence imaging strategies has emerged as a powerful tool for the specific detection and visualization of biomolecules, particularly in the context of bacterial infections. These strategies leverage the intrinsic fluorescence of nucleotide bases or modified bases for real-time monitoring of molecular interactions in living cells. Additionally, aptamers can be conjugated with various fluorescent dyes, such as organic dyes, quantum dots, and near-infrared dyes, to enhance imaging performance. A notable advancement in this field is the integration of fluorescence lifetime imaging microscopy (FLIM), which measures the decay time of fluorescence emissions. This approach provides valuable information about the local environment of fluorophores and enables differentiation between bound and unbound states of aptamer-target complexes. FLIM has been successfully employed to detect specific bacterial targets, such as Staphylococcus aureus and Escherichia coli , using aptamers designed to exhibit altered fluorescence lifetimes upon binding to their targets ( Luo et al., 2012 ; Qazi et al., 2024 ). Despite their many advantages, including versatility, and the capability for real-time monitoring, challenges remain, such as aptamer stability, non-specific binding, and fluorophore photobleaching. Continued advancements in aptamer design and imaging technologies are essential for expanding their application in biomedical research and diagnostics, particularly in complex biological systems. In this study, we developed a fluorescence imaging assay for the detection of P. aeruginosa , using a single-stranded DNA (ssDNA) aptamer, named F23 ( Wang et al., 2011 ). Additionally, we implemented robust yet user-friendly automated identification technique using the open-access software ImageJ. This approach enables the quantification of P. aeruginosa detection from confocal microscopy images of live or fixed stained bacteria, even within heterogeneous bacterial population. Our analytical method is both precise and versatile. This study also raised the question of aptamer’s selectivity against a range of bacterial strains, beyond Pseudomonas aeruginosa . 2. MATERIALS AND METHODS 2.1. Materials Different bacterial strains were used in this study: Pseudomonas aeruginosa ATCC15692 (named Pa ), Staphylococcus aureus HG001, Bacillus subtilis ATCC23857, Escherichia Coli BW25663, Pseudomonas aeruginosa ATCC15692 containing the transposon plasmid pUT18T-miniTn7 gfp ( Pa-gfp ) encoded gene for Green Fluorescent Protein (GFP) as described ( Koch et al., 2001 ), Staphylococcus epidermidis ATCC35983, different clinical isolates of Pseudomonas aeruginosa (named Pa-B5, Pa-B25, Pa-E25, Pa-F1 ) ( Cramer et al., 2012 ). Klebsiella pneumoniae, Acinetobacter baumannii, Staphylococcus haemolyticus, and Corynebacterium striatum strains were obtained from the collection of Strasbourg University Hospital. Burkholderia multivorans and Stenotrophomonas maltophilia were obtained from Anne Doleans-Jordheim collection of Centre International de Recherche en Infectiologie, Université Lyon 1. SYTO9 green fluorescent nucleic acid stains with an excitation/emission of 485/498 nm, was purchased from ThermoFisher Scientific™ (US). The solution of 4’,6-diamidino-2-phenylindole 2HC1 (DAPI) with an excitation/emission of 359/452 nm and Mueller Hinton II broth (MH) were purchased from Sigma-Aldrich (Hamburg, Germany). The ssDNA F23 aptamer previously described ( Wang et al., 2011 ) was conjugated to cyanine5 (Cy5-F23) at its 5’ end by Eurogentec (Seraing, Belgium). 2.2. Bacterial culture preparation The bacteria strains were inoculated from frozen bacterial stocks. All strains were grown overnight in MH broth without antibiotics, except Pa-gfp which was cultivated with 1 μg /ml gentamicin at 37°C under shaking at 220 rpm. The OD at 600 (OD 600 ) was adjusted to 0.2 and cells were re-suspended in fresh MH medium. The cultures were then incubated until they reached an OD 600 of 1. In all experiments, bacteria were diluted when they were in the logarithmic growth phase. The cells were then pelleted by centrifugation at 12,000 rpm for 3 min, to remove the media and, resuspended in fresh MH medium. 2.3. Fluorescence-based aptamer-labeling assays on fixed bacteria cells Bacteria were incubated in 4% paraformaldehyde (PFA) (Sigma Aldrich ®, USA) at room temperature (RT) for 30-60 min. The fixed samples were diluted in 250 mM Glycine for 5-10 min at RT, to ensure efficient quenching. After fixation, cells were washed twice with DPBS 1x (Dulbecco’s Phosphate-Buffered Saline, LONZA), centrifuged at 12,000 rpm for 10 min at RT and resuspended in 500 μL of hybridization buffer (50 mM Tris HCl pH 7.4, 5 mM KCl, 100 mM NaCl, 1mM MgCl 2 and 0,1% NaN 3 ). All the bacteria used for this study were labeled either with 10 μg/ml of DAPI or SYTO9 dyes in the dark at RT. Excess dye was removed by washing the cells three times with DPBS 1X, and centrifugation at 12,000 rpm for 3 min at RT. The cells were then transferred to microscope slides (Epredia™, Superfrost Plus, Thermo scientific) and dried for 10-30 minutes at 37°C. Figure 1A illustrates the aptamer-based labelling process of fixed bacteria cells. Download figure Open in new tab Figure 1: Schematic presentation of the experimental process used for fluorescence-based labeling assays on fixed and live bacteria cells. A . Bacteria fixed with 4 % PFA were labeled with DAPI or SYTO9, placed on microscope slides, and dried at 37 °C, treated with hybridization buffer containing BSA and tRNA to block non-specific binding sites and incubated with 1 μM Cy5-F23 aptamer at room temperature (RT). Excess aptamer was removed by washing with DPBS 1x, and the cells were fixed with 4 % PFA, washed, and mounted. B . Live bacteria were suspended with hybridization buffer containing BSA and tRNA, incubated with 1 μM of the Cy5-F23 aptamer at RT and then fixed with 4 % PFA before labeling with DAPI. Further steps in the experiment are common to both experimental processes. The cells were then immobilized to microscope slides, before visualization with confocal microscope. Ten μl of hybridization buffer containing bovine serum albumin (BSA) 10 mg/mL, (Sigma Aldrich) and transfer RNA (tRNA) at 1 μg/mL was added for saturation and incubated for 15 min at RT. The Cy5-F23 aptamer was denatured at 95°C for 5 min, cooled immediately on ice for 5 min, before dilution at 1 μM in hybridization buffer. The Cy5-F23 aptamer was then incubated with fixed cells at RT in a dark room for 60 minutes. After washes with DPBS 1x, 4% PFA was added for 45 min for fixation. After 2 washes with DPBS 1X, and drying, coverslips were mounted using Fluoromount-G™ mounting medium (E140370; Fluoromount-G™, ThermoFisher Scientific™, US). 2.4. Fluorescence-based aptamer-labeling assays on living bacterial cells The protocol for experiments on live bacteria followed the sample procedure as described above with the exception that bacterial strains were not fixed with 4% PFA before aptamer labeling. After culture preparation, bacteria were resuspended in 10 μl of hybridization buffer containing BSA and tRNA, at the above concentrations. Aptamer Cy5-F23 at 1 μM was incubated in Eppendorf tubes with the living cells for 60 min at 37 °C. After incubation, cells were washed with DPBS 1x and centrifuged for 1 min at 12,000 rpm. The bacteria were subsequently fixed with 4% PFA for 45 min and washed. For staining, DAPI was added at 10 μg/mL for 60 min. The samples were then deposited onto microscope slides and dried at 37 °C. Slides were stored in the dark. Figure 1B illustrates this process on living bacteria cells. 2.5. Confocal experiments Images were acquired using a Leica TCS SPE II confocal microscope (Leica Microsystems, Heidelberg, Germany) equipped with HCX PL APO 60x/1.40 oil objective. The confocal microscope was optimally configured for three channels DAPI/SYTO9 or GFP/Cy5 excited with three laser lines with wavelengths of 405 nm/488 nm/635 nm, respectively. Image analysis was performed using macro developed with ImageJ software ( Schneider et al., 2012 ) as described in the result section. 2.6. Aptamer stability assay Aptamer Cy5-F23 at 5 μM in hybridization buffer, MH medium, or MH containing P. aeruginosa (OD 600 of 1) were incubated at 37 °C for 0, 0.5, 2, 5, 10, 24, 48 and 72 hours. Samples were diluted in Blue/Orange Loading Dye (Promega, Madison, WI, USA), denatured at 95°C for 5 min, and loaded on 12% polyacrylamide 8 M urea denaturing gels. Gels were then stained with the Stains all cationic carbocyanine dye (Sigma-Aldrich). Each measurement was performed from three independent experiments. Gel images were taken using Sapphire Biomolecular Imager and analyzed using ImageJ software (v1.54g). All data, analyzed with GraphPad Prism version 5.04, are represented as mean ± SEM. 3. RESULTS 3.1. Stability Assay Prior conducting microscopy experiments, we evaluated the stability of the F23 aptamer under different conditions ( Figure 2 ). The F23 aptamer at a concentration of 5 μM was first incubated in the hybridization buffer at 37 °C for 0, 0.5, 2, 5, 10, 24, 48 and 72 h, then loaded on a denaturing 8M urea 12% polyacrylamide gel. The gel displayed a single band corresponding to the full-length aptamer, with no degradation products visible even after 72 hours at 37°C. Quantitative analyses of three independent experiments, confirmed that the F23 aptamer remains highly stable over an extended period of 72h at physiological temperature. While the aptamers were used in hybridization buffer for this study, future applications may involve more complex environments. To explore this, we also tested the stability of the F23 aptamer in Mueller Hinton II medium (MH), commonly used for bacterial culture both alone an in the presence of P. aeruginosa . The results showed that the aptamer remains highly stable for 72 hours ( Figure 2 ). This stability at physiological temperature suggests that the Cy5-F23 aptamer could be suitable for extended applications in biological and clinical settings, where consistent performance over time is critical. Download figure Open in new tab Figure 2: Stability analysis of the Cy5-F23 aptamer. The aptamer Cy5-F23 was incubated at 5 μM for 0, 0.5, 2, 5, 10, 24, 48 and 72 h at 37 °C in hybridization buffer, Mueller Hinton (MH) medium, and MH with P. aeruginosa . Samples were loaded on denaturing (8M urea) 12% polyacrylamide gel, revealed using the cationic Stains all solution. A . Representative image. One single band indicates that no degradation is detected. B . Quantification. Band intensity was quantified using ImageJ at each time point and expressed as a percentage. Data shown are mean ± SD of three independent experiments. 3.2. Validation of F23 aptamer binding to Pseudomonas aeruginosa strains though confocal imaging A few studies, such as those by Du et al., Geng et al., and Song et al. ( Du et al., 2020 ; Geng et al., 2021 ; Song et al., 2017 ), have depicted aptamer binding to bacterial cells using imaging. Building on this knowledge, our primary objective was to confirm the binding of the ssDNA F23 aptamer ( Wang et al., 2011 ) to P. aeruginosa using confocal microscopy. The P. aeruginosa strain was fixed using 4% paraformaldehyde, washed, and stained. For staining, we used the two nucleic acid dyes DAPI or SYTO9, both of which are commonly applied to stain live and fixed bacteria. Additionally, we utilized the GFP-labeled strain Pa (referred to as Pa-gfp) which carries the transposon plasmid pUT18T-miniTn7 gfp encoding the GFP gene ( Koch et al., 2001 ). Since the different bacterial strains were subsequently combined in cocktails later in the study, different strain were labeled with distinct dyes to enable differentiation. We investigated these staining methods to evaluate whether bacterial labeling influenced aptamer detection and subsequent quantification. The fixed bacteria were incubated with 1 μM of the F23 aptamer conjugated at its 5’ extremity to the cyanine 5 fluorophore, referred to as Cy5-F23. The bacteria cells were then washed to remove unbound aptamer and imaged using confocal microscopy. The results are presented in Figure 3A-C . Regardless the staining method used (DAPI, SYTO9 or GFP), the images demonstrated strong and overlapping fluorescence signals from the aptamer and the DAPI/SYTO9/GFP labeled P. aeruginosa , indicating highly effective binding of the F23 aptamer. In the merged images, the colocalization of the F23 aptamer and P. aeruginosa cells was evident. Yellow signals were observed when green fluorescence (from SYTO9 or GFP-labeled P. aeruginosa ) overlapped with the red fluorescence of the Cy5-F23 aptamer ( Figure 3A and 3C ). Similarly, violet signals resulted from the superposition of blue fluorescence (DAPI-stained P. aeruginosa ) with the red Cy5-F23 aptamer fluorescence ( Figure 3B ). A few red-only cells in the merged images corresponded to P. aeruginosa labeled by the Cy5-F23 aptamer but either unlabeled or weakly labeled with SYTO9, highlighting the aptamer’s robust binding and labeling capabilities even in the absence of strong SYTO9 staining. To assess selectivity, the binding of the Cy5-F23 aptamer to Staphylococcus aureus ( S. aureus ) was also evaluated using the same methodology. As shown in Figure 3D , no fluorescence signal was detected in the Cy5 channel, confirming that the Cy5-F23 aptamer did not bind to S. aureus . Due to the highly distinct fluorescence patterns observed with P. aeruginosa and S. aureus bacteria, we selected the F23 aptamer for further investigation of its specificity against additional bacterial strains and for quantification. For this purpose, we developed the macro described below. Download figure Open in new tab Figure 3: Representative confocal images of F23 aptamer on the two bacteria strains P. aeruginosa and S. aureus . One μM of the F23 aptamer conjugated to the cyanine-5 fluorophore (Cy5-F23) was incubated for 60 min with fixed strains of Pseudomonas aeruginosa , referred as Pa ( A-C ) and Staphylococcus aureus , referred as Sa ( D ). Pa was stained with A . SYTO9 (λex = 498 nm, represented in green), B . DAPI (λex = 412 nm, represented in blue). In C . the GFP-tagged Pa strain, Pa-gfp , was used (λex = 498 nm, represented in green). In A-C , the positive binding of the Cy5-F23 aptamer on Pa is represented in red (Cy5, λex = 644 nm). On the merged channels, the yellow ( A and C ) or violet ( B ) colors show the superposition of the fluorescence emitted by the dyes or GFP with that in red emitted by the F23 aptamer. The rare red bacteria which subsist on merged images represents Pa labeled by the F23 aptamer but either not marked or only weakly marked by dyes or GFP. D . Sa stained with DAPI (represented in blue). No fluorescence is emitted in the Cy5 channel because the Cy5-F23 aptamer does not bind to Sa . A-D . Images were acquired with a Leica TCS-SPE confocal microscope. Scale bar: 5 μm. Magnified images are from the inserts. 3.3. Macro development for the quantification of aptamers labeling bacteria using ImageJ, with code availability A set of imageJ macros that requires ImageJ v1.54g or higher was developed to analyze each image and quantify aptamer binding on stained bacteria. The workflow for using the macro is illustrated in Figure 4 . Source code and documentation for the installation and use of macros are available at in supplementary data. Download figure Open in new tab Figure 4. Schematic representation of the custom-developed macros used for the quantifying confocal microscopy images obtained from the aptamer-based labeling of bacterial cells. A . Images from confocal microscope are acquired and then processed for analysis using the open-source ImageJ. B . Image segmentation: segmentation is performed using the adaptive thresholding method for DAPI and SYTO9/GFP channel and classic thresholding for Cy5 channel. Identification numbers are assigned to individual bacteria, regions of interest (ROIs) are extracted and saved in the ROI manager. C . Colocalization of resulting binary images: surface overlap is measured between bacteria tag (DAPI or SYTO9/GFP) and aptamer label (Cy5) for each bacteria. D . Bacterial cell classification: bacteria are classified into the following classes: I. DAPI-bacteria non labelled with aptamer, II. DAPI-bacteria labelled with aptamer, III. P. aeruginosa labelled with aptamer, IV. P. aeruginosa non labelled with aptamer. Feature extraction is performed and quantification results in .tsv file format of classification cells belonging to each class is given. E . Batch mode. The analysis can also be run in batch mode to process large image sets. All segmented and classified cell-type images are included in the output. All macros share the same segmentation technique inspired by the adaptative thresholding method ( Abdolhoseini et al., 2019 ). Images were first denoised using a gaussian filter, followed by background subtraction. Local maximas were then defined and used as seeds for growing regions. Each resulting area was binarized using its own threshold defined by the Otsu algorithm. A watershed algorithm was applied to separate touching bacteria. A size filter was used to exclude large regions containing several bacteria. The densely confluent parts of the bacteria population were excluded from this analysis. A first classification macro ( Aptamers_Pseudo_Specificity_test . ijm) was developed to assess the selectivity of aptamer for Pseudomonas bacteria. This macro was applied to Pseudomonas (SYTO9/GFP channel) and other selected strains (DAPI channel) both individually and in mixtures, to evaluate the aptamer’s ability to identify bacteria (Cy5 channel). The DAPI and GFP channels were both segmented using an adaptative threshold method. An aptamer positive mask was then created using a simple Otsu threshold. Bacteria were considered positive for aptamer labelling if 60% or more of their area overlap this mask. The 60% threshold was set considering the bacteria drift due to convection in the media between the acquisition of different channels. The second macro ( Aptamers_Pseudo_Classifier . ijm ) was designed to spot P. aeruginosa in a mixed bacterial population, in which the whole heterogeneous bacterial mixture was labelled with DAPI and Cy5-aptamer. Images were segmented and classified using the same method as described for the first macro. Identification numbers were assigned to individual bacteria, regions of interest (ROIs), were extracted and saved separately in ROI manager, and classification categories were quantified. Binding efficiency of the aptamer to bacterial cells was then analyzed by comparing labeled and unlabeled groups, with statistical analysis used to determine significance. For large datasets, batch processing was implemented to automate the analysis. Results, including segmented images, ROIs, and classification data, were saved, and a report was generated, documenting all parameters used for reproducibility, alongside the images. 3.4. Bioimaging detection and quantification of different fixed bacteria strains The Cy5-F23 aptamer was evaluated for its binding capacity to bacterial strains beyond P. aeruginosa ( Pa ) and S. aureus ( Sa ), in order to assess its broader potential for bacteria detection. In detail, the selectivity of Cy5-F23 was tested on the following strains: (i) the model Gram-positive and Gram-negative strains Bacillus subtilis ( Bs ) and Escherichia coli ( Ec ), (ii) some of the major bacteria from the skin microbiota Staphylococcus epidermis ( Se ), Staphylococcus haemolyticus ( Sh ), Corynebacterium striatum ( Cs ), (iii) different clinical isolates of the Gram-negative bacteria strains Pseudomonas aeruginosa referred as Pa-B5, Pa-B25, Pa - E25, Pa - F1 ,, and (iv) different strains involved in infections of Cystic Fibrosis patients like Burkholderia multivorans ( Bm ), Stenotrophomonas maltophilia ( Sm ), Klebsiella pneumonia ( Kp ), Acinetobacter baumannii ( Ab ). All Pseudomonas strains were either stained with SYTO9 or were GFP-labeled, while the remaining bacterial strains were stained with DAPI. The binding capacity of the Cy5-F23 aptamer was examined on these strains. Figure 5 shows representative single confocal images for each tested bacterial strain, alongside corresponding quantitative binding data analyzed using the custom macro described in the previous chapter. Figure 6 summarizes the overall quantification, based on the analysis of all analyzed images, corresponding to 3,000-32,000 bacteria quantified / strain. The results, as shown in Figures 5 and 6 , are organized into three groups based on the F23 aptamer bacterial-binding efficiency: A. low binding, B. high binding, and C. moderate binding. This comprehensive analysis highlights the variability of the Cy5-F23 aptamer’s binding across different bacterial species, providing valuable insights into its potential application for bacterial detection. Download figure Open in new tab Figure 5: F23 aptamer binding assay on different bacterial strains. Confocal microscopy images and quantification on A . bacteria which bind weakly to the Cy5-F23 aptamer: Staphylococcus aureus ( Sa ), Staphylococcus epidermidis ( Se ), Staphylococcus haemolyticus (Sh), Klebsiella pneumoniae ( Kp ), Corynebacterium striatum (Cs), Escherichia coli ( Ec ), Acinetobacter baumannii ( Ab ), B . bacteria which bind strongly the Cy5-F23 aptamer: Pseudomonas aeruginosa (Pa) , GFP-tagged Pa ( Pa-gfp ) and different Pseudomonas aeruginosa clinical isolates referred as ( Pa-B5, Pa-B25, Pa-E25, Pa-F1 ), C . bacteria which bind partially to the Cy5-F23 aptamer: Bacillus subtilis ( Bs ), Stenotrophomonas maltophilia ( Sm ), Burkholderia multivorans ( Bm ). A-C . Briefly, 1 μM of the Cy5-F23 aptamer was incubated for 60 min with fixed bacterial strains. Images were acquired with a Leica TCS-SPE confocal microscope. All Pseudomonas strains were stained in green (SYTO9/GFP, λex = 498 nm) and all the other strains were stained in blue (DAPI, λex = 419 nm). A positive binding of the aptamer is shown in red (Cy5, λex = 644 nm). The numbers indicate the ratio of the number of aptamer-labeled bacteria for each strain to the total number of bacteria analyzed in the image (e.g., 0/522 for S. aureus ). Scale bar: 5 μm. Magnified images are from the inserts. Download figure Open in new tab Figure 6. Global quantification of the Cy5-F23 aptamer binding on different bacterial strains. Binding percentages were calculated from the number of cells labeled with the Cy5-F23 aptamer relative to the total number of cells analyzed. Bacterial strains are classified in 3 groups as defined in the text: A. Low binding, B. High binding and C. Moderate binding. Bacterial strains are also distinguished by two colors: blue for Gram-negative strains and orange for Gram-positive strains, and bacterial shapes are distinguished by two patterns: gingham for rod-shaped and horizontal stripes for round bacteria. The table summarizes the number of cells analyzed and the corresponding aptamer-binding percentages for each strain. P. aeruginosa ( Pa ) exhibited the highest binding efficiency (99.67%), while S. haemolyticus ( Sh ) had the lowest (0.22%). Bacteria with low binding (below 5%) to the F23 aptamer ( Figures 5A and 6A ) include S. aureus (as already shown in Figures 3 ), S. epidermidi s, S. haemolyticus, E. coli, C. striatum, K. pneumoniae , and A. baumannii . The Cy5-F23 aptamer does not bind to any tested Staphylococcus strain. For S. aureus , DAPI staining revealed numerous blue-fluorescent bacteria, confirming the presence of bacterial DNA. However, the Cy5 and merged fluorescence channels showed no evidence of aptamer labeling, with only DAPI-induced blue fluorescence observed. Quantitatively, none of the 522 analyzed S. aureus cells were labeled by the aptamer (0/522). Similar results were observed for the other strains: S. epidermidis (12/741), S. hemolyticus (3/344), K. pneumoniae (4/598), C. striatum (0/228), E. coli (1/516), and A. baumannii (1/271). The global quantitative analysis conducted on a larger set of images ( Figure 6A ) corroborates this observation showing negligible binding of the Cy5-F23 aptamer to these strains: 2.45% for K. pneumoniae , 1.51% for A. baumannii , 1.25% for C. striatum , 1.08% for S. epidermidis , 0.52% for E. coli , 0.49 % for S. aureus , and 0.22% for S. haemolyticus . All P. aeruginosa strains exhibited green fluorescence with consistent fluorescence patterns observed across different genotypes ( Figure 5B ). The merged images displayed yellow-orange fluorescence, resulting from the overlap of the green signal ( Pa ) and the red signal (Cy5-F23 aptamer), confirming the colocalization of the aptamer with P. aeruginosa cells. In some regions of the merged images, red fluorescence was observed, corresponding to P. aeruginosa cells bound by the Cy5-F23 aptamer but either unlabeled or only weakly labeled with SYTO9. This finding highlights the aptamer’s ability to label P. aeruginosa even when SYTO9 staining is low or absent, as previously noted. The quantitative analysis of all confocal images ( Figure 6B ) revealed that out of a total of 31,971 P. aeruginosa cells examined, 31,865 were labeled by the F23 aptamer, representing a very high binding rate of 99.67%. For the clinical strains, the binding rate is 92 to 95 %. These results underscore the high specificity of the Cy5-F23 aptamer for detecting P. aeruginosa . Among the group showing low to moderate binding of the F23 aptamer ( Figure 5C ) with efficiencies comprised between 5% and 35%, are B. subtilis (76/246), S. maltophilia ( Sm , 110/318), and B. multivorans (21/285). The global results obtained from analyzing all images ( Figure 6C ) support these observations, with aptamer-labeling rates of 31.27 % for S. maltophilia , 27.43 % for B. subtilis , and 5.94 % for B. multivorans . These results highlight the variability of the F23 aptamer’s binding between different bacterial strains. The observed discrepancies may result from differences in surface structures or molecular targets among the strains, which could influence the aptamer’s recognition or accessibility. Gaining a deeper understanding of structural and molecular variations is likely crucial for optimizing the use of aptamers in strain-specific detection or therapeutic applications. 3.5. Bioimaging detection and quantification of heterogeneous bacteria populations in mixed samples Having demonstrated that the F23 aptamer can accurately distinguish between P. aeruginosa and S. aureus in homogeneous samples, we next used the Aptamers_Pseudo_Classifier . ijm macro to assess its ability to identify its bacterial target within a heterogeneous bacterial population. In these experiments, P. aeruginosa were stained with SYTO9, while other bacterial cells were stained with DAPI. Following staining, bacteria were washed to remove excess dyes, mixed, placed on the microscope slide, incubated for 1 hour with the Cy5-F23 aptamer at room temperature and then mounted for visualization under the microscope. In a heterogeneous community of P. aeruginosa and S. aureus ( Figure 7A ), the F23 aptamer exhibited selective binding to P. aeruginosa . Red fluorescence resulting from the binding of the Cy5-F23 aptamer was observed exclusively for P. aeruginosa cells, which appeared yellow-orange in the merged image. Quantitative analysis revealed strong binding with 255 out of 278 P. aeruginosa cells labeled with aptamers. In contrast, S. aureus displayed only blue fluorescence from DAPI staining with no red signal from the Cy5-F23 aptamer (0/122). Across all analyzed images (Table in Figure 7 ), only 6 out of 1,258 Sa cells (0.46%) showed aptamer labeling, compared to 3,300 out of 3,531 P. aeruginosa cells (93.46%). These results confirm the high specificity of the F23 aptamer for P. aeruginosa , and its lack of labeling of S. aureus , even within heterogenous bacterial populations. Download figure Open in new tab Figure 7. Confocal microscopy imaging of the F23 aptamer on heterogeneous populations of fixed bacteria strains. P. aeruginosa ( Pa ) was labelled with SYTO9 (represented in green), and all the other bacteria used for this experiment were labelled with DAPI (represented in blue). One μM of the Cy5-F23 aptamer was incubated for 60 min with a cocktail of different strains: A . P. aeruginosa ( Pa ) and S. aureus ( Sa ). B . P. aeruginosa ( Pa ), S. aureus ( Sa ), S. epidermidis (Se), S. haemolitycus ( Sh ), C. striatum ( Cs ). A positive binding with the aptamer in the merged images is shown in yellow-orange color. The F23 aptamer only binds to P. aeruginosa in these mixture of bacteria. Scale bar: 5 μm. Magnified images are from the inserts. The table lists the total number of cells analyzed and the corresponding aptamer-binding percentages for each strain. The selectivity of the F23 aptamer was further validated in a more complex mixture, where P. aeruginosa cells were stained with SYTO9, while S. aureus, S. epidermidis, S. haemolyticus and C. striatum were stained with DAPI ( Figure 7B ). The F23 aptamer exclusively bound to P. aeruginosa , with no Cy5 labeling observed for the other bacterial strains, which remain distinctly blue. The yellow-orange fluorescence in the merged image confirms the specific binding of the F23 aptamer to P. aeruginosa . These results are quantitatively supported by binding rates of blue stained bacteria S. aureus, S. epidermidis, S. haemolyticus, C. striatum , with 0 out of 36 cells labeled with the Cy5-F23 aptamer. In contrast, the aptamer effectively targeted nearly all P. aeruginosa cells, with a binding rate of 360 out of 379 cells. The macro analysis further underscores the potential of the Cy5-F23 aptamer for detecting over 88 % of P. aeruginosa in heterogeneous bacterial populations, demonstrating its high specificity and suitability for complex sample environments. 3.6. Bioimaging of F23 Aptamer on living bacterial strains Experiments were conducted on live DAPI-labeled P. aeruginosa and S. aureus strains to evaluate whether the F23 aptamer maintained its binding ability with both PFA-fixed and live bacteria. For live cell experiments, P. aeruginosa and S. aureus cells were incubated at RT for 1 hour with the Cy5-F23 aptamer at 1 μM, before fixation and DAPI-labeling. The image analysis ( Figure 8A-B ) confirms the specificity of the F23 aptamer for P. aeruginosa . The aptamer labeled only the DAPI-stained P. aeruginosa , with 305 out of 383 cells showing positive binding. In contrast, no aptamer-binding was detected on live S. aureus (0/277). Quantitative analysis of 4,204 P. aeruginosa and 6,767 S. aureus , further support these findings: 73.79% of live P. aeruginosa cells (3102/4204) were labelled by the Cy5-F23 aptamer, compared to only 0.06% of live S . aureus (4/6,767). Download figure Open in new tab Figure 8. Confocal microscopy analysis of F23 aptamer on living Pseudomonas aeruginosa ( Pa ) and Staphylococcus aureus ( Sa ). A . Live Sa cells, B . live Pa cells, C . live Sa + Pa heterogeneous cocktail. Briefly, living Sa or/and Pa were incubated with 1 μM of the Cy5-F23 aptamer. Bacteria were then labelled with DAPI for visualization under microscopy (represented in blue). A positive binding of the F23 aptamer is shown in red (Cy5, λex = 644 nm). Magenta bacteria in the merged images means a positive binding of the aptamer. Note that Pa and Sa can also be differentiated by their respective shapes: bacillus and cocci, respectively. Negative binding is shown for living Sa alone and in the bacteria mixture. The F23 aptamer binds only to Pa (shown in magenta). Scale bar: 5 μm. Magnified images are from the inserts. The table presents the total number of cells analyzed, along with the corresponding aptamer-binding percentages, for isolated stains of Sa and Pa , as well as for the cocktail of Pa + Sa . In a heterogeneous bacterial community containing both live P. aeruginosa and S. aureus , confocal images clearly demonstrate that the Cy5-F23 aptamer binds exclusively to P. aeruginosa ( Figure 8C ). This is evidenced by the distinct magenta fluorescence observed in 280 P. aeruginosa cells labelled by the Cy5-F23 aptamer out of a total bacteria of 388, indicating specific recognition of P. aeruginosa cells distinguishable by their bacillus morphology. These results underscore the high specificity of the F23 aptamer for live P. aeruginosa , even in the presence of other live bacterial species. 4. DISCUSSION Accurately measuring bacterial populations is critical across various microbiological fields, including public health, biotechnology, food safety, water quality, pharmaceuticals, and environmental research ( Lebaron et al., 1998 ). However, the precise identification of specific bacterial species within complex bacteria communities (heterogeneous strains) remains a considerable challenge. Nucleic-acid aptamers have not yet been extensively studied for bacterial detection. In 2011, Wang et al. ( Wang et al., 2011 ) selected single-stranded DNA (ssDNA) aptamers targeting Pseudomonas aeruginosa using a whole-bacterium SELEX strategy. After 15 rounds of selection with Pseudomonas aeruginosa ATCC 27853 as the target, and Stenotrophomonas maltophilia ATCC 13637 and Acinetobacter baumannii ATCC 17978 for negative selection steps, they identified the F23 aptamer as the most affine aptamer with a dissociation constant K D of 17.27 ± 5.00 nM. The study also introduced the first application of aptamer-based fluorescence in situ hybridization (aptamer-FISH) for detecting ethanol-fixed bacteria, using the conjugated fluorescein isothiocyanate (FITC) F23 aptamer as the detection probe. The binding of the fluorescent F23 aptamer to P. aeruginosa was confirmed through hybridization against multiple P. aeruginosa reference strains, as well as other Pseudomonas species, including Pseudomonas fluorescens, Pseudomonas putida and Pseudomonas stutzeri . Additional testing against other closely related Gram-negative and Gram-positive species including Acinetobacter baumannii, Stenotrophomonas maltophilia, Klebsiella pneumoniae, Escherichia coli and Staphylococcus aureus demonstrated no detectable fluorescence. The fluorescence intensities observed for the four P. aeruginosa strains were similar, while no fluorescent light was detected when hybridizing with the three Pseudomonas strains and the five other bacterial species sus-mentioned. As the study by Wang et al. was not primarily focused on bioimaging, it included a single representative confocal fluorescence image of P. aeruginosa labeled with the F23 aptamer. Subsequent studies have utilized the F23 aptamer for various diagnostic and therapeutic applications, as detailed in a recent comprehensive review on aptamers targeting P. aeruginosa ( Gutiérrez-Santana and Coria-Jiménez, 2024 ), but none of those are related to quantitative bioimaging. In our study, we used the cyanine 5-conjugated F23 aptamer to detect and quantify different bacterial species through confocal imaging. The approach employed for detecting both fixed and live bacteria strains is illustrated in Figure 1 . This innovative method is the first of its kind, enabling precise quantification of fluorescent aptamer binding to multiple bacteria strains. The process was supported by a quantitative analysis framework using an open-source macro, which is freely available. This macro standardizes bacterial detection in bioimaging studies involving fluorescent aptamers. Its versatility and adaptability make it a powerful tool for quantifying bacterial binding in studies utilizing other fluorescent ligands than aptamers, such as antibodies or peptides. Our results encompass a total of 181,985 analyzed bacteria, with an average of 409 bacteria per analyzed image and a maximum of 2,492 bacteria in a single image. Zooming in on the images demonstrates that the aptamer provides a remarkably clear signal-to-noise ratio. The data show that the F23 aptamer binds with outstanding accuracy to both laboratory and clinical strains of P. aeruginosa whether fixed or live. A striking example is illustrated in Figure 5B , where the F23 aptamer successfully labels 1122 out of 1123 bacteria in a single image, highlighting the high sensitivity of this quantitative detection method. We also demonstrated that the F23 aptamer does not detect the Gram-positive S. aureus, S. haemolyticus, S. epidermidis , and C. striatum , as well as the Gram-negative K. pneumonia and E. coli , with detection rates below 3%. Interestingly, F23 provides thus an interesting tool to differentiate P. aeruginosa from S. aureus (one major pathogen affecting cystic fibrosis patients), and from different strains of the skin microbiota which are important in the case of infections of patients suffering from severe burns. However, this quantitative method also revealed partial binding of the F23 aptamer to the Gram-positive B. subtilis (27.43%) and to the Gram-negative S. maltophilia (31.27%) and to a lesser extent B. multivorans (5.94%). The confocal images in Figure 5C show that the detection is specifically targeted at certain bacteria among others, rather than portions of the image, highlighting the consistency and precision of the technique. The binding of the Cy5-F23 aptamer to S. maltophilia was unexpected. The F23 aptamer was identified through the SELEX (systematic evolution of ligands by exponential enrichment) process ( Ellington and Szostak, 1990 ). During SELEX, interfering sequences in the nucleic-acid library are removed through negative selection (also known as counter selection), while specific sequences are enriched through positive selection on the target of interest. In the study by Wang et al ( Wang et al., 2011 ), the nucleic acid library was incubated with the target P. aeruginosa , and counter-selection steps were realized to avoid cross-binding with the non-target bacteria, S. maltophilia ATCC 13637 and A. baumannii ATCC 17978 during the 12th and 14th SELEX cycles. However, the strains referred to by Wang et al. ( Wang et al., 2011 ) and in our study are different, which suggests that aptamer binding may differ between strains, even within the same species. This could also be attributed to incomplete elimination of cross-reactive sequences or similarities in surface molecular epitopes among S. maltophilia , and P. aeruginosa . This could also be attributed to the higher aptamer concentration used in our protocol (1 μM compared to 400 nM in Wang et al.) and our optimized approach, which uses PFA for fixed cells but avoids the use of alcohol. PFA fixation might indeed have a low influence on aptamer binding as detection of P. aeruginosa is slightly higher on PFA-fixed cells compared to live cells. Our results also indicate that the F23 aptamer binding is not associated with bacterial classification as Gram-positive or Gram-negative, nor with bacterial morphology (round or rod-shape). Further research is needed to identify the molecular target of the F23 aptamer and to elucidate the observed and quantified differences in binding. It is also possible that some of the tested bacterial populations are not homogeneous, and that the F23 aptamer can distinguish subtle variations between strains. Diagnostic aptamers could hold significant potential for visualizing and quantifying contaminating bacteria within ostensibly homogeneous populations or detecting pathogenic bacteria in various contexts, such as food/beverage safety, environment care, human health. Additionally, aptamers can serve as valuable tools for molecular imaging and therapeutic monitoring in bacterial infections, and even therapeutic applications ( Ye et al., 2024 ). Despite their promise, aptamers still face notable challenges that must be addressed to enhance their performance in bacterial detection, with stability and selectivity being key limitations. First, the F23 aptamer’s stability is evidenced by its resistance to degradation ( Figure 2 ), which is essential for preserving its binding ability and efficacy. Second, regarding selectivity, this study, along with others in different contexts such as the detection of cell-surface biomarkers ( Kelly et al., 2021 ) or low molecular weight compounds ( Bottari et al., 2020 ) highlights the need for further improvement to enhance aptamer performance. This could be achieved through optimization of the selection process. To address cross-reactivity and further refine the selection of aptamers, more stringent counter-selection steps have to be considered during the SELEX process, with a clear focus on aptamer ultimate intended application and usage conditions (e.g., medium, pH, temperature). This could involve using higher concentrations of non-targeted molecules or incorporating a broader range of bacterial strains and species during counter-selection. Additionally, varying environmental conditions, such as pH levels and ionic strengths, could help eliminate less selective aptamers. Structural comparisons and epitope mapping can further aid in identifying unique surface epitopes, thereby reducing the likelihood of cross-binding to non-specific strains. Targeting smaller and distinct epitopes, and accounting for glycosylation differences between bacterial strains, can help improve aptamer specificity ( Kohlberger and Gadermaier, 2022 ; Li et al., 2021 ; Zhuo et al., 2017 ). The integration of next-generation sequencing (NGS) into the SELEX process has become a routinely practice for analyzing aptamer pools post-selection ( Kolm et al., 2020 ). NGS allows for the refinement of aptamer pools, favoring sequences with high specificity and reduced cross reactivity. By adopting these strategies, the selectivity of aptamers can be significantly enhanced, thereby improving their utility for precise therapeutic and diagnostic applications. CONCLUSION Unlike existing FISH probes, which often require costly or complex steps such as peptide nucleic acid (PNA) probes or antibodies, aptamer-FISH combines both cost-effectiveness and simplicity. Our novel approach, which integrates aptamer-FISH with quantitative bioimaging analysis, improves bacterial detection and identification, making it particularly valuable for future diagnostic applications. Since it does not require permeabilization steps, this aptamer-based method is simpler and more convenient than traditional DNA-based FISH techniques. Additionnaly, it provides a cost-effective alternative compared to PCR-based assays, which rely on target genes, primer sequences, DNA extraction procedures, and detection methods ( Yamamoto, 2002 ). More importantly, it offers additional insights, such as cell counts, morphology and the ability to differentiate heterogeneous populations in situ . This quantitative aptamer-FISH method represents a promising alternative for the efficient detection of bacteria in both clinical and environmental settings. Stability remains a critical factor, and the demonstrated robustness of aptamers in complex media further highlights their potential for extended applications. Beyond diagnostics, selective aptamers are promising ligands for innovative therapeutic strategies, including targeted antimicrobial therapies and precision drug delivery systems to combat P. aeruginosa infections. Furthermore, our versatile aptamer-based quantitative detection platform could easily be adapted for other clinically relevant bacterial pathogens, and to other fluorescent molecular tools, broadening its applicability. By integrating this approach with advanced biosensing systems or microfluidic devices, its performance in point-of-care settings could be further optimized, paving the way for highly efficient and versatile diagnostic solutions. FUNDING This research was financially supported by the French Ministry of Europe and Foreign Affairs, the Ministry of Higher Education, Research and Innovation, the French Institute of Rabat (PHC MAGHREB 2022 Grant No 47455NH and PHC Toubkal 2019 Grant No 41520SE), the University of Strasbourg (IdEx Emergence 2017-974-3), and the Moroccan National Center for Scientific and Technical Research (CNRST). C.M. was financed by the MAScIR - Moroccan Foundation for Advanced Science, Innovation and Research, and by the PHC Maghreb program. B.A. was financed by the MAScIR, and by the PHC Toubkal program. AUTHOR CONTRIBUTIONS Conceptualization, P.F. and L.C.; Methodology, C.M., R.V., B.A., H.AB., M.O., P.F. and L.C.; Formal analysis, C.M., R.V., P.F. and L.C.; Investigation, P.F. and L.C.; Writing—original draft preparation, C.M., R.V., P.F. and L.C.; Writing, C.M, and L.C.; Project administration, P.F, and L.C.; Funding acquisition, P.F, and L.C. All authors have read and agreed to this version of the manuscript. DATA AVAILABILITY STATEMENT Data supporting reported results will be provided by corresponding author upon request. CONFLICT OF INTEREST The authors declare no conflict of interest. ACKNOWLEDGMENT We thank A. Doleans Jordheim, B. Tümmler, and A. Grillon for the gift of bacterial isolates. We gratefully acknowledge the Imaging Center PIQ-QuESt ( https://piq.unistra.fr/ ), member of the national infrastructure France Bioimaging, supported by the French National Research Agency ANR-10-INSB-04. ABBREVIATIONS BSA bovine serum albumin Cy5 cyanine 5 DAPI 4’,6-diamidino-2-phenylindole 2HC1 DPBS Dulbecco’s phosphate-buffered saline FISH fluorescence in situ hybridization GFP green fluorescent protein MH Mueller Hinton II medium OD optical density PFA paraformaldehyde RT room temperature tRNA transfer RNA REFERENCES ↵ Abdolhoseini , M. , Kluge , M.G. , Walker , F.R. , Johnson , S.J. , 2019 . Segmentation of Heavily Clustered Nuclei from Histopathological Images . Sci. Rep . 9 , 4551 . doi: 10.1038/s41598-019-38813-2 OpenUrl CrossRef ↵ Afrasiabi , S. , Pourhajibagher , M. , Raoofian , R. , Tabarzad , M. , Bahador , A. , 2020 . Therapeutic applications of nucleic acid aptamers in microbial infections . J. Biomed. Sci . 27 . doi: 10.1186/s12929-019-0611-0 OpenUrl CrossRef ↵ Batani , G. , Bayer , K. , Böge , J. , Hentschel , U. , Thomas , T. , 2019 . Fluorescence in situ hybridization (FISH) and cell sorting of living bacteria . Sci. Rep . 9 , 18618 . doi: 10.1038/s41598-019-55049-2 OpenUrl CrossRef PubMed ↵ Bergkessel , M. , Forte , B. , Gilbert , I.H. , 2023 . Small-Molecule Antibiotic Drug Development: Need and Challenges . ACS Infect. Dis . 9 , 2062 – 2071 . doi: 10.1021/acsinfecdis.3c00189 OpenUrl CrossRef PubMed ↵ Botelho , J. , Grosso , F. , Peixe , L. , 2019 . Antibiotic resistance in Pseudomonas aeruginosa - Mechanisms, epidemiology and evolution . Drug Resist. Updat. Rev. Comment. Antimicrob. Anticancer Chemother . 44 , 100640 . doi: 10.1016/j.drup.2019.07.002 OpenUrl CrossRef PubMed ↵ Bottari , F. , Daems , E. , de Vries , A.-M. , Van Wielendaele , P. , Trashin , S. , Blust , R. , Sobott , F. , Madder , A. , Martins , J.C. , De Wael , K. , 2020 . Do Aptamers Always Bind? The Need for a Multifaceted Analytical Approach When Demonstrating Binding Affinity between Aptamer and Low Molecular Weight Compounds . J. Am. Chem. Soc . 142 , 19622 – 19630 . doi: 10.1021/jacs.0c08691 OpenUrl CrossRef PubMed ↵ Cramer , N. , Wiehlmann , L. , Ciofu , O. , Tamm , S. , Høiby , N. , Tümmler , B. , 2012 . Molecular Epidemiology of Chronic Pseudomonas aeruginosa Airway Infections in Cystic Fibrosis . PLoS ONE 7 , e50731 . doi: 10.1371/journal.pone.0050731 OpenUrl CrossRef PubMed ↵ Deusenbery , C. , Wang , Y. , Shukla , A. , 2021 . Recent Innovations in Bacterial Infection Detection and Treatment . ACS Infect. Dis . 7 , 695 – 720 . doi: 10.1021/acsinfecdis.0c00890 OpenUrl CrossRef PubMed ↵ Du , X. , Wang , W. , Wu , C. , Jia , B. , Li , W. , Qiu , L. , Jiang , P. , Wang , J. , Li , Y.-Q. , 2020 . Enzyme-responsive turn-on nanoprobes for in situ fluorescence imaging and localized photothermal treatment of multidrug-resistant bacterial infections . J. Mater. Chem. B 8 , 7403 – 7412 . doi: 10.1039/d0tb00750a OpenUrl CrossRef PubMed ↵ Ellington , A.D. , Szostak , J.W. , 1990 . In vitro selection of RNA molecules that bind specific ligands . Nature 346 , 818 – 822 . doi: 10.1038/346818a0 OpenUrl CrossRef PubMed Web of Science ↵ Geng , Z. , Cao , Z. , Liu , R. , Liu , K. , Liu , J. , Tan , W. , 2021 . Aptamer-assisted tumor localization of bacteria for enhanced biotherapy . Nat. Commun . 12 , 6584 . doi: 10.1038/s41467-021-26956-8 OpenUrl CrossRef PubMed ↵ Gopinath , S.C.B. , Kumar , P.K.R. , 2013 . Aptamers that bind to the hemagglutinin of the recent pandemic influenza virus H1N1 and efficiently inhibit agglutination . Acta Biomater . 9 , 8932 – 8941 . doi: 10.1016/j.actbio.2013.06.016 OpenUrl CrossRef PubMed ↵ Gu , J. , Wang , H. , Zhang , M. , Xiong , Y. , Yang , L. , Ren , B. , Huang , R. , 2022 . Application of Fluorescence In Situ Hybridization (FISH) in Oral Microbial Detection . Pathogens 11 , 1450 . doi: 10.3390/pathogens11121450 OpenUrl CrossRef PubMed ↵ Guan , B. , Zhang , X. , 2020 . Aptamers as Versatile Ligands for Biomedical and Pharmaceutical Applications . Int. J. Nanomedicine 15 , 1059 – 1071 . doi: 10.2147/IJN.S237544 OpenUrl CrossRef PubMed ↵ Gutiérrez-Santana , J.C. , Coria-Jiménez , V.R. , 2024 . Diagnosis and Therapeutic Strategies Based on Nucleic Acid Aptamers Selected against Pseudomonas aeruginosa: The Challenge of Cystic Fibrosis . ChemMedChem 19 , e202300544 . doi: 10.1002/cmdc.202300544 OpenUrl CrossRef PubMed ↵ Hameed , S. , Xie , L. , Ying , Y. , 2018 . Conventional and emerging detection techniques for pathogenic bacteria in food science: A review . Trends Food Sci. Technol . 81 , 61 – 73 . doi: 10.1016/j.tifs.2018.05.020 OpenUrl CrossRef ↵ Jangra , V. , Sharma , N. , Chhillar , A.K. , 2022 . Therapeutic approaches for combating Pseudomonas aeruginosa infections . Microbes Infect . 24 , 104950 . doi: 10.1016/j.micinf.2022.104950 OpenUrl CrossRef PubMed ↵ Jenison , R.D. , Gill , S.C. , Pardi , A. , Polisky , B. , 1994 . High-Resolution Molecular Discrimination by RNA . Science 263 , 1425 – 1429 . doi: 10.1126/science.7510417 OpenUrl Abstract / FREE Full Text ↵ Kelly , L. , Maier , K.E. , Yan , A. , Levy , M. , 2021 . A comparative analysis of cell surface targeting aptamers . Nat. Commun . 12 , 6275 . doi: 10.1038/s41467-021-26463-w OpenUrl CrossRef PubMed ↵ Koch , B. , Jensen , L.E. , Nybroe , O. , 2001 . A panel of Tn7-based vectors for insertion of the gfp marker gene or for delivery of cloned DNA into Gram-negative bacteria at a neutral chromosomal site . J. Microbiol. Methods 45 , 187 – 195 . doi: 10.1016/s0167-7012(01)00246-9 OpenUrl CrossRef PubMed Web of Science ↵ Kohlberger , M. , Gadermaier , G. , 2022 . SELEX: Critical factors and optimization strategies for successful aptamer selection . Biotechnol. Appl. Biochem . 69 , 1771 – 1792 . doi: 10.1002/bab.2244 OpenUrl CrossRef ↵ Kolm , C. , Cervenka , I. , Aschl , U.J. , Baumann , N. , Jakwerth , S. , Krska , R. , Mach , R.L. , Sommer , R. , DeRosa , M.C. , Kirschner , A.K.T. , Farnleitner , A.H. , Reischer , G.H. , 2020 . DNA aptamers against bacterial cells can be efficiently selected by a SELEX process using state-of-the art qPCR and ultra-deep sequencing . Sci. Rep . 10 , 20917 . doi: 10.1038/s41598-020-77221-9 OpenUrl CrossRef PubMed ↵ Lebaron , P. , Parthuisot , N. , Catala , P. , 1998 . Comparison of Blue Nucleic Acid Dyes for Flow Cytometric Enumeration of Bacteria in Aquatic Systems . Appl. Environ. Microbiol . 64 , 1725 – 1730 . OpenUrl Abstract / FREE Full Text ↵ Léguillier , V. , Heddi , B. , Vidic , J. , 2024 . Recent Advances in Aptamer-Based Biosensors for Bacterial Detection . Biosensors 14 , 210 . doi: 10.3390/bios14050210 OpenUrl CrossRef PubMed ↵ Li , H.-Y. , Jia , W.-N. , Li , X.-Y. , Zhang , L. , Liu , C. , Wu , J. , 2020 . Advances in detection of infectious agents by aptamer-based technologies . Emerg. Microbes Infect . 9 , 1671 – 1681 . doi: 10.1080/22221751.2020.1792352 OpenUrl CrossRef PubMed ↵ Li , W. , Ma , Y. , Guo , Z. , Xing , R. , Liu , Z. , 2021 . Efficient Screening of Glycan-Specific Aptamers Using a Glycosylated Peptide as a Scaffold . Anal. Chem . 93 , 956 – 963 . doi: 10.1021/acs.analchem.0c03675 OpenUrl CrossRef PubMed ↵ Lin , B. , Xiao , F. , Jiang , J. , Zhao , Z. , Zhou , X. , 2023 . Engineered aptamers for molecular imaging . Chem. Sci . 14 , 14039 – 14061 . doi: 10.1039/D3SC03989G OpenUrl CrossRef PubMed ↵ Luo , F. , Zheng , L. , Chen , S. , Cai , Q. , Lin , Z. , Qiu , B. , Chen , G. , 2012 . An aptamer-based fluorescence biosensor for multiplex detection using unmodified gold nanoparticles . Chem. Commun. Camb. Engl . doi: 10.1039/c2cc32667a OpenUrl CrossRef ↵ Moter , A. , Göbel , U.B. , 2000 . Fluorescence in situ hybridization (FISH) for direct visualization of microorganisms . J. Microbiol. Methods 41 , 85 – 112 . doi: 10.1016/s0167-7012(00)00152-4 OpenUrl CrossRef PubMed Web of Science ↵ Qazi , R.A. , Aman , N. , Ullah , N. , Jamila , N. , Bibi , N. , 2024 . Recent advancement for enhanced e. Coli detection in electrochemical biosensors . Microchem. J . 196 , 109673 . doi: 10.1016/j.microc.2023.109673 OpenUrl CrossRef ↵ Qin , S. , Xiao , W. , Zhou , C. , Pu , Q. , Deng , X. , Lan , L. , Liang , H. , Song , X. , Wu , M. , 2022 . Pseudomonas aeruginosa: pathogenesis, virulence factors, antibiotic resistance, interaction with host, technology advances and emerging therapeutics . Signal Transduct. Target. Ther . 7 , 1 – 27 . doi: 10.1038/s41392-022-01056-1 OpenUrl CrossRef PubMed ↵ Rasoulinejad , S. , Gargari , S.L.M. , 2016 . Aptamer-nanobody based ELASA for specific detection of Acinetobacter baumannii isolates . J. Biotechnol . 231 , 46 – 54 . doi: 10.1016/j.jbiotec.2016.05.024 OpenUrl CrossRef PubMed ↵ Rudd , K.E. , Johnson , S.C. , Agesa , K.M. , Shackelford , K.A. , Tsoi , D. , Kievlan , D.R. , Colombara , D.V. , Ikuta , K.S. , Kissoon , N. , Finfer , S. , Fleischmann-Struzek , C. , Machado , F.R. , Reinhart , K.K. , Rowan , K. , Seymour , C.W. , Watson , R.S. , West , T.E. , Marinho , F. , Hay , S.I. , Lozano , R. , Lopez , A.D. , Angus , D.C. , Murray , C.J.L. , Naghavi , M. , 2020 . Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study . Lancet Lond. Engl . 395 , 200 – 211 . doi: 10.1016/S0140-6736(19)32989-7 OpenUrl CrossRef PubMed ↵ Schneider , C.A. , Rasband , W.S. , Eliceiri , K.W. , 2012 . NIH Image to ImageJ: 25 years of image analysis . Nat. Methods 9 , 671 – 675 . doi: 10.1038/nmeth.2089 OpenUrl CrossRef PubMed Web of Science ↵ Song , K.-M. , Lee , S. , Ban , C. , 2012 . Aptamers and their biological applications . Sensors 12 , 612 – 631 . doi: 10.3390/s120100612 OpenUrl CrossRef PubMed Web of Science ↵ Song , M.Y. , Nguyen , D. , Hong , S.W. , Kim , B.C. , 2017 . Broadly reactive aptamers targeting bacteria belonging to different genera using a sequential toggle cell-SELEX . Sci. Rep . 7 , 43641 . doi: 10.1038/srep43641 OpenUrl CrossRef PubMed ↵ Taneja , V. , Goel , M. , Shankar , U. , Kumar , A. , Khilnani , G.C. , Prasad , H.K. , Prasad , G.B.K.S. , Gupta , U.D. , Sharma , T.K. , 2020 . An Aptamer Linked Immobilized Sorbent Assay (ALISA) to Detect Circulatory IFN-α, an Inflammatory Protein among Tuberculosis Patients . ACS Comb. Sci . 22 , 656 – 666 . doi: 10.1021/acscombsci.0c00108 OpenUrl CrossRef PubMed ↵ Tuon , F.F. , Dantas , L.R. , Suss , P.H. , Tasca Ribeiro , V.S. , 2022 . Pathogenesis of the Pseudomonas aeruginosa Biofilm: A Review . Pathog. Basel Switz . 11 , 300 . doi: 10.3390/pathogens11030300 OpenUrl CrossRef PubMed ↵ Wang , K.-Y. , Zeng , Y.-L. , Yang , X.-Y. , Li , W.-B. , Lan , X.-P. , 2011 . Utility of aptamer-fluorescence in situ hybridization for rapid detection of Pseudomonas aeruginosa . Eur. J. Clin. Microbiol. Infect. Dis . 30 , 273 – 278 . doi: 10.1007/s10096-010-1074-0 OpenUrl CrossRef PubMed ↵ Wang , L. , Wang , R. , Wei , H. , Li , Y. , 2018 . Selection of aptamers against pathogenic bacteria and their diagnostics application . World J. Microbiol. Biotechnol . 34 , 149 . doi: 10.1007/s11274-018-2528-2 OpenUrl CrossRef PubMed ↵ Yamamoto , Y. , 2002 . PCR in diagnosis of infection: detection of bacteria in cerebrospinal fluids . Clin. Diagn. Lab. Immunol . 9 , 508 – 514 . doi: 10.1128/cdli.9.3.508-514.2002 OpenUrl CrossRef PubMed ↵ Ye , Z. , Chen , H. , Weinans , H. , van der Wal , B. , Rios , J.L. , 2024 . Novel Aptamer Strategies in Combating Bacterial Infections: From Diagnostics to Therapeutics . Pharmaceutics 16 , 1140 . doi: 10.3390/pharmaceutics16091140 OpenUrl CrossRef PubMed ↵ Zhang , S. , Wang , Q. , Ning , J. , Wang , W. , 2023 . Nucleic acid strand displacement for indirect determination of foodborne bacteria by capillary electrophoresis and its application in antagonism and bacteriostasis studies . Electrophoresis . doi: 10.1002/elps.202300155 OpenUrl CrossRef ↵ Zhou , J. , Rossi , J. , 2017 . Aptamers as targeted therapeutics: current potential and challenges . Nat. Rev. Drug Discov . 16 , 181 – 202 . doi: 10.1038/nrd.2016.199 OpenUrl CrossRef PubMed ↵ Zhuo , Z. , Yu , Y. , Wang , M. , Li , J. , Zhang , Z. , Liu , J. , Wu , X. , Lu , A. , Zhang , G. , Zhang , B. , 2017 . Recent Advances in SELEX Technology and Aptamer Applications in Biomedicine . Int. J. Mol. Sci . 18 , 2142 . doi: 10.3390/ijms18102142 OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted February 07, 2025. Download PDF Supplementary Material 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 Bioimaging with fluorescent nucleic-acid aptamers for the specific detection and quantification of Pseudomonas aeruginosa alone and in heterogeneous bacterial populations 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 Bioimaging with fluorescent nucleic-acid aptamers for the specific detection and quantification of Pseudomonas aeruginosa alone and in heterogeneous bacterial populations Chaimae Mezouarhi , Romain Vauchelles , Basma Abdallah , Janel Régine , Mouna Ouadghiri , Hassan Ait Benhassou , Pierre Fechter , Laurence Choulier bioRxiv 2025.02.07.636672; doi: https://doi.org/10.1101/2025.02.07.636672 Share This Article: Copy Citation Tools Bioimaging with fluorescent nucleic-acid aptamers for the specific detection and quantification of Pseudomonas aeruginosa alone and in heterogeneous bacterial populations Chaimae Mezouarhi , Romain Vauchelles , Basma Abdallah , Janel Régine , Mouna Ouadghiri , Hassan Ait Benhassou , Pierre Fechter , Laurence Choulier bioRxiv 2025.02.07.636672; doi: https://doi.org/10.1101/2025.02.07.636672 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 (7622) Biochemistry (17647) Bioengineering (13868) Bioinformatics (41875) Biophysics (21422) Cancer Biology (18552) Cell Biology (25458) Clinical Trials (138) Developmental Biology (13364) Ecology (19866) Epidemiology (2067) Evolutionary Biology (24290) Genetics (15589) Genomics (22475) Immunology (17710) Microbiology (40324) Molecular Biology (17144) Neuroscience (88469) Paleontology (666) Pathology (2826) Pharmacology and Toxicology (4815) Physiology (7635) Plant Biology (15112) Scientific Communication and Education (2042) Synthetic Biology (4286) Systems Biology (9814) Zoology (2268)