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507000.9813Sequence-specific DNA solid-phase extraction in an on-chip monolith: Towards detection of antibiotic resistance genes. Antibiotic resistance of bacteria is a growing problem and presents a challenge for prompt treatment in patients with sepsis. Currently used methods rely on culturing or amplification; however, these steps are either time consuming or suffer from interference issues. A microfluidic device was made from black polypropylene, with a monolithic column modified with a capture oligonucleotide for sequence selective solid-phase extraction of a complementary target from a lysate sample. Porous properties of the monolith allow flow and hybridization of a target complementary to the probe immobilized on the column surface. Good flow-through properties enable extraction of a 100μL sample and elution of target DNA in 12min total time. Using a fluorescently labeled target oligonucleotide related to Verona Integron-Mediated Metallo-β-lactamase it was possible to extract and detect a 1pM sample with 83% recovery. Temperature-mediated elution by heating above the duplex melting point provides a clean extract without any agents that interfere with base pairing, allowing various labeling methods or further downstream processing of the eluent. Further integration of this extraction module with a system for isolation and lysis of bacteria from blood, as well as combining with single-molecule detection should allow rapid determination of antibiotic resistance.201728734608
508410.9810Cloth-based hybridization array system for the identification of antibiotic resistance genes in Salmonella. A simple macroarray system based on the use of polyester cloth as the solid phase for DNA hybridization has been developed for the identification and characterization of bacteria on the basis of the presence of various virulence and toxin genes. In this approach, a multiplex polymerase chain reaction (PCR) incorporating digoxigenin-dUTP is used to simultaneously amplify different marker genes, with subsequent rapid detection of the amplicons by hybridization with an array of probes immobilized on polyester cloth and immunoenzymatic assay of the bound label. As an example of the applicability of this cloth-based hybridization array system (CHAS) in the characterization of foodborne pathogens, a method has been developed enabling the detection of antibiotic resistance and other marker genes associated with the multidrug-resistant food pathogen Salmonella enterica subsp. enterica serotype Typhimurium DT104. The CHAS is a simple, cost-effective tool for the simultaneous detection of amplicons generated in a multiplex PCR, and the concept is broadly applicable to the identification of key pathogen-specific marker genes in bacterial isolates.200718363231
512520.9809Do we still need Illumina sequencing data? Evaluating Oxford Nanopore Technologies R10.4.1 flow cells and the Rapid v14 library prep kit for Gram negative bacteria whole genome assemblies. The best whole genome assemblies are currently built from a combination of highly accurate short-read sequencing data and long-read sequencing data that can bridge repetitive and problematic regions. Oxford Nanopore Technologies (ONT) produce long-read sequencing platforms and they are continually improving their technology to obtain higher quality read data that is approaching the quality obtained from short-read platforms such as Illumina. As these innovations continue, we evaluated how much ONT read coverage produced by the Rapid Barcoding Kit v14 (SQK-RBK114) is necessary to generate high-quality hybrid and long-read-only genome assemblies for a panel of carbapenemase-producing Enterobacterales bacterial isolates. We found that 30× long-read coverage is sufficient if Illumina data are available, and that more (at least 100× long-read coverage is recommended for long-read-only assemblies. Illumina polishing is still improving single nucleotide variants (SNVs) and INDELs in long-read-only assemblies. We also examined if antimicrobial resistance genes could be accurately identified in long-read-only data, and found that Flye assemblies regardless of ONT coverage detected >96% of resistance genes at 100% identity and length. Overall, the Rapid Barcoding Kit v14 and long-read-only assemblies can be an optimal sequencing strategy (i.e., plasmid characterization and AMR detection) but finer-scale analyses (i.e., SNV) still benefit from short-read data.202438354391
907630.9808ResiDB: An automated database manager for sequence data. The amount of publicly available DNA sequence data is drastically increasing, making it a tedious task to create sequence databases necessary for the design of diagnostic assays. The selection of appropriate sequences is especially challenging in genes affected by frequent point mutations such as antibiotic resistance genes. To overcome this issue, we have designed the webtool resiDB, a rapid and user-friendly sequence database manager for bacteria, fungi, viruses, protozoa, invertebrates, plants, archaea, environmental and whole genome shotgun sequence data. It automatically identifies and curates sequence clusters to create custom sequence databases based on user-defined input sequences. A collection of helpful visualization tools gives the user the opportunity to easily access, evaluate, edit, and download the newly created database. Consequently, researchers do no longer have to manually manage sequence data retrieval, deal with hardware limitations, and run multiple independent software tools, each having its own requirements, input and output formats. Our tool was developed within the H2020 project FAPIC aiming to develop a single diagnostic assay targeting all sepsis-relevant pathogens and antibiotic resistance mechanisms. ResiDB is freely accessible to all users through https://residb.ait.ac.at/.202133495705
512440.9804Oxford nanopore long-read sequencing enables the generation of complete bacterial and plasmid genomes without short-read sequencing. INTRODUCTION: Genome-based analysis is crucial in monitoring antibiotic-resistant bacteria (ARB)and antibiotic-resistance genes (ARGs). Short-read sequencing is typically used to obtain incomplete draft genomes, while long-read sequencing can obtain genomes of multidrug resistance (MDR) plasmids and track the transmission of plasmid-borne antimicrobial resistance genes in bacteria. However, long-read sequencing suffers from low-accuracy base calling, and short-read sequencing is often required to improve genome accuracy. This increases costs and turnaround time. METHODS: In this study, a novel ONT sequencing method is described, which uses the latest ONT chemistry with improved accuracy to assemble genomes of MDR strains and plasmids from long-read sequencing data only. Three strains of Salmonella carrying MDR plasmids were sequenced using the ONT SQK-LSK114 kit with flow cell R10.4.1, and de novo genome assembly was performed with average read accuracy (Q > 10) of 98.9%. RESULTS AND DISCUSSION: For a 5-Mb-long bacterial genome, finished genome sequences with accuracy of >99.99% could be obtained at 75× sequencing coverage depth using Flye and Medaka software. Thus, this new ONT method greatly improves base-calling accuracy, allowing for the de novo assembly of high-quality finished bacterial or plasmid genomes without the need for short-read sequencing. This saves both money and time and supports the application of ONT data in critical genome-based epidemiological analyses. The novel ONT approach described in this study can take the place of traditional combination genome assembly based on short- and long-read sequencing, enabling pangenomic analyses based on high-quality complete bacterial and plasmid genomes to monitor the spread of antibiotic-resistant bacteria and antibiotic resistance genes.202337256057
588150.9803A novel universal DNA labeling and amplification system for rapid microarray-based detection of 117 antibiotic resistance genes in Gram-positive bacteria. A rapid and simple DNA labeling system has been developed for disposable microarrays and has been validated for the detection of 117 antibiotic resistance genes abundant in Gram-positive bacteria. The DNA was fragmented and amplified using phi-29 polymerase and random primers with linkers. Labeling and further amplification were then performed by classic PCR amplification using biotinylated primers specific for the linkers. The microarray developed by Perreten et al. (Perreten, V., Vorlet-Fawer, L., Slickers, P., Ehricht, R., Kuhnert, P., Frey, J., 2005. Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria. J.Clin.Microbiol. 43, 2291-2302.) was improved by additional oligonucleotides. A total of 244 oligonucleotides (26 to 37 nucleotide length and with similar melting temperatures) were spotted on the microarray, including genes conferring resistance to clinically important antibiotic classes like β-lactams, macrolides, aminoglycosides, glycopeptides and tetracyclines. Each antibiotic resistance gene is represented by at least 2 oligonucleotides designed from consensus sequences of gene families. The specificity of the oligonucleotides and the quality of the amplification and labeling were verified by analysis of a collection of 65 strains belonging to 24 species. Association between genotype and phenotype was verified for 6 antibiotics using 77 Staphylococcus strains belonging to different species and revealed 95% test specificity and a 93% predictive value of a positive test. The DNA labeling and amplification is independent of the species and of the target genes and could be used for different types of microarrays. This system has also the advantage to detect several genes within one bacterium at once, like in Staphylococcus aureus strain BM3318, in which up to 15 genes were detected. This new microarray-based detection system offers a large potential for applications in clinical diagnostic, basic research, food safety and surveillance programs for antimicrobial resistance.201525451460
907860.9801MetaCherchant: analyzing genomic context of antibiotic resistance genes in gut microbiota. MOTIVATION: Antibiotic resistance is an important global public health problem. Human gut microbiota is an accumulator of resistance genes potentially providing them to pathogens. It is important to develop tools for identifying the mechanisms of how resistance is transmitted between gut microbial species and pathogens. RESULTS: We developed MetaCherchant-an algorithm for extracting the genomic environment of antibiotic resistance genes from metagenomic data in the form of a graph. The algorithm was validated on a number of simulated and published datasets, as well as applied to new 'shotgun' metagenomes of gut microbiota from patients with Helicobacter pylori who underwent antibiotic therapy. Genomic context was reconstructed for several major resistance genes. Taxonomic annotation of the context suggests that within a single metagenome, the resistance genes can be contained in genomes of multiple species. MetaCherchant allows reconstruction of mobile elements with resistance genes within the genomes of bacteria using metagenomic data. Application of MetaCherchant in differential mode produced specific graph structures suggesting the evidence of possible resistance gene transmission within a mobile element that occurred as a result of the antibiotic therapy. MetaCherchant is a promising tool giving researchers an opportunity to get an insight into dynamics of resistance transmission in vivo basing on metagenomic data. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are freely available for download at https://github.com/ctlab/metacherchant. The code is written in Java and is platform-independent. COTANCT: ulyantsev@rain.ifmo.ru. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.201829092015
974170.9801ARGai 1.0: A GAN augmented in silico approach for identifying resistant genes and strains in E. coli using vision transformer. The emergence of infectious disease and antibiotic resistance in bacteria like Escherichia coli (E. coli) shows the necessity for novel computational techniques for identifying essential genes that contribute to resistance. The task of identifying resistant strains and multi-drug patterns in E. coli is a major challenge with whole genome sequencing (WGS) and next-generation sequencing (NGS) data. To address this issue, we suggest ARGai 1.0 a deep learning architecture enhanced with generative adversarial networks (GANs). We mitigate data scarcity difficulties by augmenting limited experimental datasets with synthetic data generated by GANs. Our in-silico method (augmentation with feature selection) improves the identification of resistance genes in E. coli by using feature extraction techniques to identify valuable features from actual and GAN-generated data. Employing comprehensive validation, we exhibit the effectiveness of our ARGai 1.0 in precisely identifying the informative and resistant genes. In addition, our ARGai 1.0 identifies the resistant strains with a classification accuracy of 98.96 % on Deep Convolutional Generative Adversarial Network (DCGAN) augmented data. Additionally, ARGai 1.0 achieves more than 98 % of sensitivity and specificity. We also benchmark our ARGai 1.0 with several state-of-the-art AI models for resistant strain classification. In the fight against antibiotic resistance, ARGai 1.0 offers a promising avenue for computational genomics. With implications for research and clinical practice, this work shows the potential of deep networks with GAN augmentation as a practical and successful method for gene identification in E. coli.202539813877
35480.9800New cloning vectors to facilitate quick allelic exchange in gram-negative bacteria. New cloning vectors have been developed with features to enhance quick allelic exchange in gram-negative bacteria. The conditionally replicative R6K and transfer origins facilitate conjugation and chromosomal integration into a variety of bacterial species, whereas the sacB gene provides counterselection for allelic exchange. The vectors have incorporated the lacZ alpha fragment with an enhanced multicloning site for easy blue/white screening and priming sites identified for efficient in vivo assembly or other DNA assembly cloning techniques. Different antibiotic resistance markers allow versatility for use with different bacteria, and transformation into an Escherichia coli strain capable of conjugation enables a quick method for allelic exchange. As a proof of principle, the authors used these vectors to inactivate genes in Vibrio cholerae and Salmonella typhimurium.202133492170
377190.9800RFPlasmid: predicting plasmid sequences from short-read assembly data using machine learning. Antimicrobial-resistance (AMR) genes in bacteria are often carried on plasmids and these plasmids can transfer AMR genes between bacteria. For molecular epidemiology purposes and risk assessment, it is important to know whether the genes are located on highly transferable plasmids or in the more stable chromosomes. However, draft whole-genome sequences are fragmented, making it difficult to discriminate plasmid and chromosomal contigs. Current methods that predict plasmid sequences from draft genome sequences rely on single features, like k-mer composition, circularity of the DNA molecule, copy number or sequence identity to plasmid replication genes, all of which have their drawbacks, especially when faced with large single-copy plasmids, which often carry resistance genes. With our newly developed prediction tool RFPlasmid, we use a combination of multiple features, including k-mer composition and databases with plasmid and chromosomal marker proteins, to predict whether the likely source of a contig is plasmid or chromosomal. The tool RFPlasmid supports models for 17 different bacterial taxa, including Campylobacter, Escherichia coli and Salmonella, and has a taxon agnostic model for metagenomic assemblies or unsupported organisms. RFPlasmid is available both as a standalone tool and via a web interface.202134846288
5123100.9800Ultrafast and Cost-Effective Pathogen Identification and Resistance Gene Detection in a Clinical Setting Using Nanopore Flongle Sequencing. Rapid bacterial identification and antimicrobial resistance gene (ARG) detection are crucial for fast optimization of antibiotic treatment, especially for septic patients where each hour of delayed antibiotic prescription might have lethal consequences. This work investigates whether the Oxford Nanopore Technology's (ONT) Flongle sequencing platform is suitable for real-time sequencing directly from blood cultures to identify bacteria and detect resistance-encoding genes. For the analysis, we used pure bacterial cultures of four clinical isolates of Escherichia coli and Klebsiella pneumoniae and two blood samples spiked with either E. coli or K. pneumoniae that had been cultured overnight. We sequenced both the whole genome and plasmids isolated from these bacteria using two different sequencing kits. Generally, Flongle data allow rapid bacterial ID and resistome detection based on the first 1,000-3,000 generated sequences (10 min to 3 h from the sequencing start), albeit ARG variant identification did not always correspond to ONT MinION and Illumina sequencing-based data. Flongle data are sufficient for 99.9% genome coverage within at most 20,000 (clinical isolates) or 50,000 (positive blood cultures) sequences generated. The SQK-LSK110 Ligation kit resulted in higher genome coverage and more accurate bacterial identification than the SQK-RBK004 Rapid Barcode kit.202235369431
9742110.9799BOCS: DNA k-mer content and scoring for rapid genetic biomarker identification at low coverage. A single, inexpensive diagnostic test capable of rapidly identifying a wide range of genetic biomarkers would prove invaluable in precision medicine. Previous work has demonstrated the potential for high-throughput, label-free detection of A-G-C-T content in DNA k-mers, providing an alternative to single-letter sequencing while also having inherent lossy data compression and massively parallel data acquisition. Here, we apply a new bioinformatics algorithm - block optical content scoring (BOCS) - capable of using the high-throughput content k-mers for rapid, broad-spectrum identification of genetic biomarkers. BOCS uses content-based sequence alignment for probabilistic mapping of k-mer contents to gene sequences within a biomarker database, resulting in a probability ranking of genes on a content score. Simulations of the BOCS algorithm reveal high accuracy for identification of single antibiotic resistance genes, even in the presence of significant sequencing errors (100% accuracy for no sequencing errors, and >90% accuracy for sequencing errors at 20%), and at well below full coverage of the genes. Simulations for detecting multiple resistance genes within a methicillin-resistant Staphylococcus aureus (MRSA) strain showed 100% accuracy at an average gene coverage of merely 0.515, when the k-mer lengths were variable and with 4% sequencing error within the k-mer blocks. Extension of BOCS to cancer and other genetic diseases met or exceeded the results for resistance genes. Combined with a high-throughput content-based sequencing technique, the BOCS algorithm potentiates a test capable of rapid diagnosis and profiling of genetic biomarkers ranging from antibiotic resistance to cancer and other genetic diseases.201931173943
5831120.9799Development of a nucleic acid lateral flow immunoassay (NALFIA) for reliable, simple and rapid detection of the methicillin resistance genes mecA and mecC. The gene mecA and its homologue mecC confer methicillin resistance in Staphylococcus aureus and other staphylococci. Methicillin-resistant staphylococci (MRS) are considered resistant to all β-lactam antibiotics. To avoid the use of β-lactam antibiotics for the control of MRS infections, there is an urgent need for a fast and reliable screening assay for mecA and mecC that can easily be integrated in routine laboratory diagnostics. The aim of this study was the development of such a rapid detection method for methicillin resistance based on nucleic acid lateral flow immunoassay (NALFIA) technology. In NALFIA, the target sequences are PCR-amplified, immobilized via antigen-antibody interaction and finally visualized as distinct black bars resulting from neutravidin-labeled carbon particles via biotin-neutravidin interaction. A screening of 60 defined strains (MRS and non-target bacteria) and 28 methicillin-resistant S. aureus (MRSA) isolates from clinical samples was performed with PCR-NALFIA in comparison to PCR with subsequent gel electrophoresis (PCR-GE) and real-time PCR. While all samples were correctly identified with all assays, PCR-NALFIA was superior with respect to limits of detection. Moreover, this assay allowed for differentiation between mecA and mecC by visualizing the two alleles at different positions on NALFIA test stripes. However, since this test system only targets the mecA and mecC genes, it does not allow to determine in which staphylococcal species the mec gene is included. Requiring only a fraction of the time needed for cultural methods (i.e. the gold standard), the PCR-NALFIA presented here is easy to handle and can be readily integrated into laboratory diagnostics.201727569992
8157130.9799Autologous DNA mobilization and multiplication expedite natural products discovery from bacteria. The transmission of antibiotic-resistance genes, comprising mobilization and relocation events, orchestrates the dissemination of antimicrobial resistance. Inspired by this evolutionarily successful paradigm, we developed ACTIMOT, a CRISPR-Cas9-based approach to unlock the vast chemical diversity concealed within bacterial genomes. ACTIMOT enables the efficient mobilization and relocation of large DNA fragments from the chromosome to replicative plasmids within the same bacterial cell. ACTIMOT circumvents the limitations of traditional molecular cloning methods involving handling and replicating large pieces of genomic DNA. Using ACTIMOT, we mobilized and activated four cryptic biosynthetic gene clusters from Streptomyces, leading to the discovery of 39 compounds across four distinct classes. This work highlights the potential of ACTIMOT for accelerating the exploration of biosynthetic pathways and the discovery of natural products.202439666857
535140.9798Improved broad-host-range plasmids for DNA cloning in gram-negative bacteria. Improved broad-host-range plasmid vectors were constructed based on existing plasmids RSF1010 and RK404. The new plasmids pDSK509, pDSK519, and pRK415, have several additional cloning sites and improved antibiotic-resistance genes which facilitate subcloning and mobilization into various Gram-negative bacteria. Several new polylinker sites were added to the Escherichia coli plasmids pUC118 and pUC119, resulting in the new plasmids, pUC128 and pUC129. These plasmids facilitate the transfer of cloned DNA fragments to the broad-host-range vectors. Finally, the broad-host-range cosmid cloning vector pLAFR3 was improved by the addition of a double cos casette to generate the new plasmid, pLAFR5. This latter cosmid simplifies vector preparation and has permitted the rapid cloning of genomic DNA fragments generated with Sau3A. The resulting clones may be introduced into other Gram-negative bacteria by conjugation.19882853689
5068150.9798Ultrasensitive Label-Free Detection of Unamplified Multidrug-Resistance Bacteria Genes with a Bimodal Waveguide Interferometric Biosensor. Infections by multidrug-resistant bacteria are becoming a major healthcare emergence with millions of reported cases every year and an increasing incidence of deaths. An advanced diagnostic platform able to directly detect and identify antimicrobial resistance in a faster way than conventional techniques could help in the adoption of early and accurate therapeutic interventions, limiting the actual negative impact on patient outcomes. With this objective, we have developed a new biosensor methodology using an ultrasensitive nanophotonic bimodal waveguide interferometer (BiMW), which allows a rapid and direct detection, without amplification, of two prevalent and clinically relevant Gram-negative antimicrobial resistance encoding sequences: the extended-spectrum betalactamase-encoding gene blaCTX-M-15 and the carbapenemase-encoding gene blaNDM-5 We demonstrate the extreme sensitivity and specificity of our biosensor methodology for the detection of both gene sequences. Our results show that the BiMW biosensor can be employed as an ultrasensitive (attomolar level) and specific diagnostic tool for rapidly (less than 30 min) identifying drug resistance. The BiMW nanobiosensor holds great promise as a powerful tool for the control and management of healthcare-associated infections by multidrug-resistant bacteria.202033086716
9073160.9798EpitoCore: Mining Conserved Epitope Vaccine Candidates in the Core Proteome of Multiple Bacteria Strains. In reverse vaccinology approaches, complete proteomes of bacteria are submitted to multiple computational prediction steps in order to filter proteins that are possible vaccine candidates. Most available tools perform such analysis only in a single strain, or a very limited number of strains. But the vast amount of genomic data had shown that most bacteria contain pangenomes, i.e., their genomic information contains core, conserved genes, and random accessory genes specific to each strain. Therefore, in reverse vaccinology methods it is of the utmost importance to define core proteins and core epitopes. EpitoCore is a decision-tree pipeline developed to fulfill that need. It provides surfaceome prediction of proteins from related strains, defines core proteins within those, calculate their immunogenicity, predicts epitopes for a given set of MHC alleles defined by the user, and then reports if epitopes are located extracellularly and if they are conserved among the core homologs. Pipeline performance is illustrated by mining peptide vaccine candidates in Mycobacterium avium hominissuis strains. From a total proteome of ~4,800 proteins per strain, EpitoCore predicted 103 highly immunogenic core homologs located at cell surface, many of those related to virulence and drug resistance. Conserved epitopes identified among these homologs allows the users to define sets of peptides with potential to immunize the largest coverage of tested HLA alleles using peptide-based vaccines. Therefore, EpitoCore is able to provide automated identification of conserved epitopes in bacterial pangenomic datasets.202032431712
9074170.9797BacAnt: A Combination Annotation Server for Bacterial DNA Sequences to Identify Antibiotic Resistance Genes, Integrons, and Transposable Elements. Whole genome sequencing (WGS) of bacteria has become a routine method in diagnostic laboratories. One of the clinically most useful advantages of WGS is the ability to predict antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) in bacterial sequences. This allows comprehensive investigations of such genetic features but can also be used for epidemiological studies. A plethora of software programs have been developed for the detailed annotation of bacterial DNA sequences, such as rapid annotation using subsystem technology (RAST), Resfinder, ISfinder, INTEGRALL and The Transposon Registry. Unfortunately, to this day, a reliable annotation tool of the combination of ARGs and MGEs is not available, and the generation of genbank files requires much manual input. Here, we present a new webserver which allows the annotation of ARGs, integrons and transposable elements at the same time. The pipeline generates genbank files automatically, which are compatible with Easyfig for comparative genomic analysis. Our BacAnt code and standalone software package are available at https://github.com/xthua/bacant with an accompanying web application at http://bacant.net.202134367079
9743180.9797Simultaneous Detection of Antibiotic Resistance Genes on Paper-Based Chip Using [Ru(phen)(2)dppz](2+) Turn-on Fluorescence Probe. Antibiotic resistance, the ability of some bacteria to resist antibiotic drugs, has been a major global health burden due to the extensive use of antibiotic agents. Antibiotic resistance is encoded via particular genes; hence the specific detection of these genes is necessary for diagnosis and treatment of antibiotic resistant cases. Conventional methods for monitoring antibiotic resistance genes require the sample to be transported to a central laboratory for tedious and sophisticated tests, which is grueling and time-consuming. We developed a paper-based chip, integrated with loop-mediated isothermal amplification (LAMP) and the "light switch" molecule [Ru(phen)(2)dppz](2+), to conduct turn-on fluorescent detection of antibiotic resistance genes. In this assay, the amplification reagents can be embedded into test spots of the chip in advance, thus simplifying the detection procedure. [Ru(phen)(2)dppz](2+) was applied to intercalate into amplicons for product analysis, enabling this assay to be operated in a wash-free format. The paper-based detection device exhibited a limit of detection (LOD) as few as 100 copies for antibiotic resistance genes. Meanwhile, it could detect antibiotic resistance genes from various bacteria. Noticeably, the approach can be applied to other genes besides antibiotic resistance genes by simply changing the LAMP primers. Therefore, this paper-based chip has the potential for point-of-care (POC) applications to detect various gene samples, especially in resource-limited conditions.201829323478
9981190.9797High-contrast imaging of cellular non-repetitive drug-resistant genes via in situ dead Cas12a-labeled PCR. In situ imaging of genes of pathogenic bacteria can profile cellular heterogeneity, such as the emergence of drug resistance. Fluorescence in situ hybridization (FISH) serves as a classic approach to image mRNAs inside cells, but it remains challenging to elucidate genomic DNAs and relies on multiple fluorescently labeled probes. Herein, we present a dead Cas12a (dCas12a)-labeled polymerase chain reaction (CasPCR) assay for high-contrast imaging of cellular drug-resistant genes. We employed a syncretic dCas12a-green fluorescent protein (dCas12a-GFP) to tag the amplicons, thereby enabling high-contrast imaging and avoiding multiple fluorescently labeled probes. The CasPCR assay can quantify quinolone-resistant Salmonella enterica in mixed populations and identify them isolated from poultry farms.202439229640