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Socea JN, Stone VN, Qian X, Gibbs PL, Levinson KJ. Implementing laboratory automation for next-generation sequencing: benefits and challenges for library preparation. Front Public Health 2023; 11:1195581. [PMID: 37521966 PMCID: PMC10373871 DOI: 10.3389/fpubh.2023.1195581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 06/15/2023] [Indexed: 08/01/2023] Open
Abstract
In the wake of COVID-19, the importance of next-generation sequencing (NGS) for diagnostic testing and surveillance-based screening has never been more evident. Considering this, continued investment is critical to ensure more public health laboratories can adopt these advanced molecular technologies. However, many facilities may face potential barriers such as limited staff available to routinely prepare, test, and analyze samples, lack of expertise or experience in sequencing, difficulties in assay standardization, and an inability to handle throughput within expected turnaround times. Workflow automation provides an opportunity to overcome many of these challenges. By identifying these types of sustainable solutions, laboratories can begin to utilize more advanced molecular-based approaches for routine testing. Nevertheless, the introduction of automation, while valuable, does not come without its own challenges. This perspective article aims to highlight the benefits and difficulties of implementing laboratory automation used for sequencing. We discuss strategies for implementation, including things to consider when selecting instrumentation, how to approach validations, staff training, and troubleshooting.
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Jamalian A, Freeke J, Chowdhary A, de Hoog GS, Stielow JB, Meis JF. Fast and Accurate Identification of Candida auris by High Resolution Mass Spectrometry. J Fungi (Basel) 2023; 9:jof9020267. [PMID: 36836381 PMCID: PMC9966097 DOI: 10.3390/jof9020267] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 02/13/2023] [Accepted: 02/13/2023] [Indexed: 02/19/2023] Open
Abstract
The emerging pathogen Candida auris has been associated with nosocomial outbreaks on six continents. Genetic analysis indicates simultaneous and independent emergence of separate clades of the species in different geographical locations. Both invasive infection and colonization have been observed, warranting attention due to variable antifungal resistance profiles and hospital transmission. MALDI-TOF based identification methods have become routine in hospitals and research institutes. However, identification of the newly emerging lineages of C. auris yet remains a diagnostic challenge. In this study an innovative liquid chromatography (LC)-high resolution OrbitrapTM mass spectrometry method was used for identification of C. auris from axenic microbial cultures. A set of 102 strains from all five clades and different body locations were investigated. The results revealed correct identification of all C. auris strains within the sample cohort, with an identification accuracy of 99.6% from plate culture, in a time-efficient manner. Furthermore, application of the applied mass spectrometry technology provided the species identification down to clade level, thus potentially providing the possibility for epidemiological surveillance to track pathogen spread. Identification beyond species level is required specially to differentiate between nosocomial transmission and repeated introduction to a hospital.
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Affiliation(s)
- Azadeh Jamalian
- Centre of Expertise in Mycology, Radboud UMC/Canisius Wilhelmina Hospital, 6532 SZ Nijmegen, The Netherlands
| | - Joanna Freeke
- Centre of Expertise in Mycology, Radboud UMC/Canisius Wilhelmina Hospital, 6532 SZ Nijmegen, The Netherlands
| | - Anuradha Chowdhary
- Medical Mycology Unit, Department of Microbiology, Vallabhbhai Patel Chest Institute, University of Delhi, Delhi 110007, India
| | - G. Sybren de Hoog
- Centre of Expertise in Mycology, Radboud UMC/Canisius Wilhelmina Hospital, 6532 SZ Nijmegen, The Netherlands
- Department of Medical Microbiology and Infectious Diseases, Canisius Wilhelmina Hospital, 6532 SZ Nijmegen, The Netherlands
| | - J. Benjamin Stielow
- Centre of Expertise in Mycology, Radboud UMC/Canisius Wilhelmina Hospital, 6532 SZ Nijmegen, The Netherlands
| | - Jacques F. Meis
- Centre of Expertise in Mycology, Radboud UMC/Canisius Wilhelmina Hospital, 6532 SZ Nijmegen, The Netherlands
- Department of Medical Microbiology and Infectious Diseases, Canisius Wilhelmina Hospital, 6532 SZ Nijmegen, The Netherlands
- Bioprocess Engineering and Biotechnology Graduate Program, Federal University of Paraná, Curitiba 80060, Brazil
- Department I of Internal Medicine, Faculty of Medicine, University of Cologne and Excellence Center for Medical Mycology, University Hospital Cologne, 50931 Cologne, Germany
- Correspondence:
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Metagenomic Antimicrobial Susceptibility Testing from Simulated Native Patient Samples. Antibiotics (Basel) 2023; 12:antibiotics12020366. [PMID: 36830277 PMCID: PMC9952719 DOI: 10.3390/antibiotics12020366] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/06/2023] [Accepted: 02/08/2023] [Indexed: 02/12/2023] Open
Abstract
Genomic antimicrobial susceptibility testing (AST) has been shown to be accurate for many pathogens and antimicrobials. However, these methods have not been systematically evaluated for clinical metagenomic data. We investigate the performance of in-silico AST from clinical metagenomes (MG-AST). Using isolate sequencing data from a multi-center study on antimicrobial resistance (AMR) as well as shotgun-sequenced septic urine samples, we simulate over 2000 complicated urinary tract infection (cUTI) metagenomes with known resistance phenotype to 5 antimicrobials. Applying rule-based and machine learning-based genomic AST classifiers, we explore the impact of sequencing depth and technology, metagenome complexity, and bioinformatics processing approaches on AST accuracy. By using an optimized metagenomics assembly and binning workflow, MG-AST achieved balanced accuracy within 5.1% of isolate-derived genomic AST. For poly-microbial infections, taxonomic sample complexity and relatedness of taxa in the sample is a key factor influencing metagenomic binning and downstream MG-AST accuracy. We show that the reassignment of putative plasmid contigs by their predicted host range and investigation of whole resistome capabilities improved MG-AST performance on poly-microbial samples. We further demonstrate that machine learning-based methods enable MG-AST with superior accuracy compared to rule-based approaches on simulated native patient samples.
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Validation and Application of Long-Read Whole-Genome Sequencing for Antimicrobial Resistance Gene Detection and Antimicrobial Susceptibility Testing. Antimicrob Agents Chemother 2023; 67:e0107222. [PMID: 36533931 PMCID: PMC9872642 DOI: 10.1128/aac.01072-22] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Next-generation sequencing applications are increasingly used for detection and characterization of antimicrobial-resistant pathogens in clinical settings. Oxford Nanopore Technologies (ONT) sequencing offers advantages for clinical use compared with other sequencing methodologies because it enables real-time basecalling, produces long sequencing reads that increase the ability to correctly assemble DNA fragments, provides short turnaround times, and requires relatively uncomplicated sample preparation. A drawback of ONT sequencing, however, is its lower per-read accuracy than short-read sequencing. We sought to identify best practices in ONT sequencing protocols. As some variability in sequencing results may be introduced by the DNA extraction methodology, we tested three DNA extraction kits across three independent laboratories using a representative set of six bacterial isolates to investigate accuracy and reproducibility of ONT technology. All DNA extraction techniques showed comparable performance; however, the DNeasy PowerSoil Pro kit had the highest sequencing yield. This kit was subsequently applied to 42 sequentially collected bacterial isolates from blood cultures to assess Ares Genetics's pipelines for predictive whole-genome sequencing antimicrobial susceptibility testing (WGS-AST) performance compared to phenotypic triplicate broth microdilution results. WGS-AST results ranged across the organisms and resulted in an overall categorical agreement of 95% for penicillins, 82.4% for cephalosporins, 76.7% for carbapenems, 86.9% for fluoroquinolones, and 96.2% for aminoglycosides. Very major errors/major errors were 0%/16.7% (penicillins), 11.7%/3.6% (cephalosporins), 0%/24.4% (carbapenems), 2.5%/7.7% (fluoroquinolones), and 0%/4.1% (aminoglycosides), respectively. This work showed that, although additional refinements are necessary, ONT sequencing demonstrates potential as a method to perform WGS-AST on cultured isolates for patient care.
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Jiang S, Chen Y, Han S, Lv L, Li L. Next-Generation Sequencing Applications for the Study of Fungal Pathogens. Microorganisms 2022; 10:microorganisms10101882. [PMID: 36296159 PMCID: PMC9609632 DOI: 10.3390/microorganisms10101882] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/13/2022] [Accepted: 09/15/2022] [Indexed: 11/16/2022] Open
Abstract
Next-generation sequencing (NGS) has become a widely used technology in biological research. NGS applications for clinical pathogen detection have become vital technologies. It is increasingly common to perform fast, accurate, and specific detection of clinical specimens using NGS. Pathogenic fungi with high virulence and drug resistance cause life-threatening clinical infections. NGS has had a significant biotechnological impact on detecting bacteria and viruses but is not equally applicable to fungi. There is a particularly urgent clinical need to use NGS to help identify fungi causing infections and prevent negative impacts. This review summarizes current research on NGS applications for fungi and offers a visual method of fungal detection. With the development of NGS and solutions for overcoming sequencing limitations, we suggest clinicians test specimens as soon as possible when encountering infections of unknown cause, suspected infections in vital organs, or rapidly progressive disease.
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Affiliation(s)
- Shiman Jiang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou 310003, China
| | - Yanfei Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou 310003, China
| | - Shengyi Han
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou 310003, China
| | - Longxian Lv
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou 310003, China
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou 310003, China
- Jinan Microecological Biomedicine Shandong Laboratory, Jinan 250021, China
- Correspondence: ; Tel.: +86-0571-8723-6458
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Parra-Flores J, Holý O, Acuña S, Lepuschitz S, Pietzka A, Contreras-Fernández A, Chavarría-Sepulveda P, Cruz-Córdova A, Xicohtencatl-Cortes J, Mancilla-Rojano J, Castillo A, Ruppitsch W, Forsythe S. Genomic Characterization of Cronobacter spp. and Salmonella spp. Strains Isolated From Powdered Infant Formula in Chile. Front Microbiol 2022; 13:884721. [PMID: 35722296 PMCID: PMC9201451 DOI: 10.3389/fmicb.2022.884721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Accepted: 05/04/2022] [Indexed: 11/14/2022] Open
Abstract
This study characterized five Cronobacter spp. and six Salmonella spp. strains that had been isolated from 155 samples of powdered infant formula (PIF) sold in Chile and manufactured in Chile and Mexico in 2018–2020. Two strains of Cronobacter sakazakii sequence type (ST) ST1 and ST31 (serotypes O:1 and O:2) and one strain of Cronobacter malonaticus ST60 (O:1) were identified. All Salmonella strains were identified as Salmonella Typhimurium ST19 (serotype O:4) by average nucleotide identity, ribosomal multilocus sequence typing (rMLST), and core genome MLST (cgMLST). The C. sakazakii and C. malonaticus isolates were resistant to cephalothin, whereas the Salmonella isolates were resistant to oxacillin and ampicillin. Nineteen antibiotic resistance genes were detected in the C. sakazakii and C. malonaticus isolates; the most prevalent were mcr-9.1, blaCSA, and blaCMA. In Salmonella, 30 genes encoding for aminoglycoside and cephalosporin resistance were identified, including aac(6′)-Iaa, β-lactamases ampH, ampC1, and marA. In the Cronobacter isolates, 32 virulence-associated genes were detected by WGS and clustered as flagellar proteins, outer membrane proteins, chemotaxis, hemolysins, invasion, plasminogen activator, colonization, transcriptional regulator, survival in macrophages, use of sialic acid, and toxin-antitoxin genes. In the Salmonella strains, 120 virulence associated genes were detected, adherence, magnesium uptake, resistance to antimicrobial peptides, secretion system, stress protein, toxin, resistance to complement killing, and eight pathogenicity islands. The C. sakazakii and C. malonaticus strains harbored I-E and I-F CRISPR-Cas systems and carried Col(pHHAD28) and IncFIB(pCTU1) plasmids, respectively. The Salmonella strains harbored type I-E CRISPR-Cas systems and carried IncFII(S) plasmids. The presence of C. sakazakii and Salmonella in PIF is a health risk for infants aged less than 6 months. For this reason, sanitary practices should be reinforced for its production and retail surveillance.
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Affiliation(s)
- Julio Parra-Flores
- Department of Nutrition and Public Health, Universidad del Bío-Bío, Chillán, Chile
| | - Ondřej Holý
- Science and Research Centre, Faculty of Health Sciences, Palacký University Olomouc, Olomouc, Czechia
| | - Sergio Acuña
- Department of Food Engineering, Universidad del Bío-Bío, Chillán, Chile
| | - Sarah Lepuschitz
- Austrian Agency for Health and Food Safety, Institute for Medical Microbiology and Hygiene, Vienna, Austria
| | - Ariane Pietzka
- Austrian Agency for Health and Food Safety, Institute for Medical Microbiology and Hygiene, Vienna, Austria
| | | | | | - Ariadnna Cruz-Córdova
- Intestinal Bacteriology Research Laboratory, Hospital Infantil de México Federico Gómez, Mexico City, Mexico
| | - Juan Xicohtencatl-Cortes
- Intestinal Bacteriology Research Laboratory, Hospital Infantil de México Federico Gómez, Mexico City, Mexico
| | - Jetsi Mancilla-Rojano
- Intestinal Bacteriology Research Laboratory, Hospital Infantil de México Federico Gómez, Mexico City, Mexico.,Faculty of Medicine, Biological Sciences Graduate Program, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Alejandro Castillo
- Department of Nutrition and Food Science, Texas A&M University, College Station, TX, United States
| | - Werner Ruppitsch
- Austrian Agency for Health and Food Safety, Institute for Medical Microbiology and Hygiene, Vienna, Austria
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Proceedings of the Clinical Microbiology Open 2018 and 2019 - a Discussion about Emerging Trends, Challenges, and the Future of Clinical Microbiology. J Clin Microbiol 2022; 60:e0009222. [PMID: 35638361 DOI: 10.1128/jcm.00092-22] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Clinical Microbiology Open (CMO), a meeting supported by the American Society for Microbiology's Clinical and Public Health Microbiology Committee (CPHMC) and Corporate Council, provides a unique interactive platform for leaders from diagnostic microbiology laboratories, industry, and federal agencies to discuss the current and future state of the clinical microbiology laboratory. The purpose is to leverage the group's diverse views and expertise to address critical challenges, and discuss potential collaborative opportunities for diagnostic microbiology, through the utilization of varied resources. The first and second CMO meetings were held in 2018 and 2019, respectively. Discussions were focused on the diagnostic potential of innovative technologies and laboratory diagnostic stewardship, including expansion of next-generation sequencing into clinical diagnostics, improvement and advancement of molecular diagnostics, emerging diagnostics, including rapid antimicrobial susceptibility and point of care testing (POCT), harnessing big data through artificial intelligence, and staffing in the clinical microbiology laboratory. Shortly after CMO 2019, the coronavirus disease 2019 (COVID-19) pandemic further highlighted the need for the diagnostic microbiology community to work together to utilize and expand on resources to respond to the pandemic. The issues, challenges, and potential collaborative efforts discussed during the past two CMO meetings proved critical in addressing the COVID-19 response by diagnostic laboratories, industry partners, and federal organizations. Planning for a third CMO (CMO 2022) is underway and will transition from a discussion-based meeting to an action-based meeting. The primary focus will be to reflect on the lessons learned from the COVID-19 pandemic and better prepare for future pandemics.
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Prosperi M, Boucher C, Bian J, Marini S. Assessing putative bias in prediction of anti-microbial resistance from real-world genotyping data under explicit causal assumptions. Artif Intell Med 2022; 130:102326. [PMID: 35809965 PMCID: PMC9425730 DOI: 10.1016/j.artmed.2022.102326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 05/11/2022] [Accepted: 05/23/2022] [Indexed: 11/02/2022]
Abstract
Whole genome sequencing (WGS) is quickly becoming the customary means for identification of antimicrobial resistance (AMR) due to its ability to obtain high resolution information about the genes and mechanisms that are causing resistance and driving pathogen mobility. By contrast, traditional phenotypic (antibiogram) testing cannot easily elucidate such information. Yet development of AMR prediction tools from genotype-phenotype data can be biased, since sampling is non-randomized. Sample provenience, period of collection, and species representation can confound the association of genetic traits with AMR. Thus, prediction models can perform poorly on new data with sampling distribution shifts. In this work -under an explicit set of causal assumptions- we evaluate the effectiveness of propensity-based rebalancing and confounding adjustment on antibiotic resistance prediction using genotype-phenotype AMR data from the Pathosystems Resource Integration Center (PATRIC). We select bacterial genotypes (encoded as k-mer signatures, i.e., DNA fragments of length k), country, year, species, and AMR phenotypes for the tetracycline drug class, preparing test data with recent genomes coming from a single country. We test boosted logistic regression (BLR) and random forests (RF) with/without bias-handling. On 10,936 instances, we find evidence of species, location and year imbalance with respect to the AMR phenotype. The crude versus bias-adjusted change in effect of genetic signatures on AMR varies but only moderately (selecting the top 20,000 out of 40+ million k-mers). The area under the receiver operating characteristic (AUROC) of the RF (0.95) is comparable to that of BLR (0.94) on both out-of-bag samples from bootstrap and the external test (n = 1085), where AUROCs do not decrease. We observe a 1 %-5 % gain in AUROC with bias-handling compared to the sole use of genetic signatures. In conclusion, we recommend using causally-informed prediction methods for modeling real-world AMR data; however, traditional adjustment or propensity-based methods may not provide advantage in all use cases and further methodological development should be sought.
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Culture-Free Detection of Antibiotic Resistance Markers from Native Patient Samples by Hybridization Capture Sequencing. Microorganisms 2021; 9:microorganisms9081672. [PMID: 34442751 PMCID: PMC8398375 DOI: 10.3390/microorganisms9081672] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 07/29/2021] [Accepted: 08/03/2021] [Indexed: 01/04/2023] Open
Abstract
The increasing incidence of antimicrobial resistance (AMR) is a major global challenge. Routine techniques for molecular AMR marker detection are largely based on low-plex PCR and detect dozens to hundreds of AMR markers. To allow for comprehensive and sensitive profiling of AMR markers, we developed a capture-based next generation sequencing (NGS) workflow featuring a novel AMR marker panel based on the curated AMR database ARESdb. Our primary objective was to compare the sensitivity of target enrichment-based AMR marker detection to metagenomics sequencing. Therefore, we determined the limit of detection (LOD) in synovial fluid and urine samples across four key pathogens. We further demonstrated proof-of-concept for AMR marker profiling from septic samples using a selection of urine samples with confirmed monoinfection. The results showed that the capture-based workflow is more sensitive and requires lower sequencing depth compared with metagenomics sequencing, allowing for comprehensive AMR marker detection with an LOD of 1000 CFU/mL. Combining the ARESdb AMR panel with 16S rRNA gene sequencing allowed for the culture-free detection of bacterial taxa and AMR markers directly from septic patient samples at an average sensitivity of 99%. Summarizing, the newly developed ARESdb AMR panel may serve as a valuable tool for comprehensive and sensitive AMR marker detection.
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Huber S, Knoll MA, Berktold M, Würzner R, Brindlmayer A, Weber V, Posch AE, Mrazek K, Lepuschitz S, Ante M, Beisken S, Orth-Höller D, Weinberger J. Genomic and Phenotypic Analysis of Linezolid-Resistant Staphylococcus epidermidis in a Tertiary Hospital in Innsbruck, Austria. Microorganisms 2021; 9:1023. [PMID: 34068744 PMCID: PMC8150687 DOI: 10.3390/microorganisms9051023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 05/06/2021] [Accepted: 05/07/2021] [Indexed: 11/17/2022] Open
Abstract
Whole genome sequencing is a useful tool to monitor the spread of resistance mechanisms in bacteria. In this retrospective study, we investigated genetic resistance mechanisms, sequence types (ST) and respective phenotypes of linezolid-resistant Staphylococcus epidermidis (LRSE, n = 129) recovered from a cohort of patients receiving or not receiving linezolid within a tertiary hospital in Innsbruck, Austria. Hereby, the point mutation G2603U in the 23S rRNA (n = 91) was the major resistance mechanism followed by the presence of plasmid-derived cfr (n = 30). The majority of LRSE isolates were ST2 strains, followed by ST5. LRSE isolates expressed a high resistance level to linezolid with a minimal inhibitory concentration of ≥256 mg/L (n = 83) in most isolates, particularly in strains carrying the cfr gene (p < 0.001). Linezolid usage was the most prominent (but not the only) trigger for the development of linezolid resistance. However, administration of linezolid was not associated with a specific resistance mechanism. Restriction of linezolid usage and the monitoring of plasmid-derived cfr in LRSE are potential key steps to reduce linezolid resistance and its transmission to more pathogenic Gram-positive bacteria.
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Affiliation(s)
- Silke Huber
- Institute of Hygiene and Medical Microbiology, Medical University of Innsbruck, 6020 Innsbruck, Austria; (S.H.); (M.A.K.); (M.B.); (R.W.)
| | - Miriam A. Knoll
- Institute of Hygiene and Medical Microbiology, Medical University of Innsbruck, 6020 Innsbruck, Austria; (S.H.); (M.A.K.); (M.B.); (R.W.)
| | - Michael Berktold
- Institute of Hygiene and Medical Microbiology, Medical University of Innsbruck, 6020 Innsbruck, Austria; (S.H.); (M.A.K.); (M.B.); (R.W.)
| | - Reinhard Würzner
- Institute of Hygiene and Medical Microbiology, Medical University of Innsbruck, 6020 Innsbruck, Austria; (S.H.); (M.A.K.); (M.B.); (R.W.)
| | - Anita Brindlmayer
- Center for Biomedical Technology, Department for Biomedical Research, Danube University Krems, 3500 Krems, Austria; (A.B.); (V.W.)
| | - Viktoria Weber
- Center for Biomedical Technology, Department for Biomedical Research, Danube University Krems, 3500 Krems, Austria; (A.B.); (V.W.)
| | - Andreas E. Posch
- Ares Genetics GmbH, 1030 Vienna, Austria; (A.E.P.); (K.M.); (S.L.); (M.A.); (S.B.); (J.W.)
| | - Katharina Mrazek
- Ares Genetics GmbH, 1030 Vienna, Austria; (A.E.P.); (K.M.); (S.L.); (M.A.); (S.B.); (J.W.)
| | - Sarah Lepuschitz
- Ares Genetics GmbH, 1030 Vienna, Austria; (A.E.P.); (K.M.); (S.L.); (M.A.); (S.B.); (J.W.)
| | - Michael Ante
- Ares Genetics GmbH, 1030 Vienna, Austria; (A.E.P.); (K.M.); (S.L.); (M.A.); (S.B.); (J.W.)
| | - Stephan Beisken
- Ares Genetics GmbH, 1030 Vienna, Austria; (A.E.P.); (K.M.); (S.L.); (M.A.); (S.B.); (J.W.)
| | | | - Johannes Weinberger
- Ares Genetics GmbH, 1030 Vienna, Austria; (A.E.P.); (K.M.); (S.L.); (M.A.); (S.B.); (J.W.)
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Barretto C, Rincón C, Portmann AC, Ngom-Bru C. Whole Genome Sequencing Applied to Pathogen Source Tracking in Food Industry: Key Considerations for Robust Bioinformatics Data Analysis and Reliable Results Interpretation. Genes (Basel) 2021; 12:275. [PMID: 33671973 PMCID: PMC7919020 DOI: 10.3390/genes12020275] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 01/28/2021] [Accepted: 02/08/2021] [Indexed: 12/31/2022] Open
Abstract
Whole genome sequencing (WGS) has arisen as a powerful tool to perform pathogen source tracking in the food industry thanks to several developments in recent years. However, the cost associated to this technology and the degree of expertise required to accurately process and understand the data has limited its adoption at a wider scale. Additionally, the time needed to obtain actionable information is often seen as an impairment for the application and use of the information generated via WGS. Ongoing work towards standardization of wet lab including sequencing protocols, following guidelines from the regulatory authorities and international standardization efforts make the technology more and more accessible. However, data analysis and results interpretation guidelines are still subject to initiatives coming from distinct groups and institutions. There are multiple bioinformatics software and pipelines developed to handle such information. Nevertheless, little consensus exists on a standard way to process the data and interpret the results. Here, we want to present the constraints we face in an industrial setting and the steps we consider necessary to obtain high quality data, reproducible results and a robust interpretation of the obtained information. All of this, in a time frame allowing for data-driven actions supporting factories and their needs.
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Affiliation(s)
- Caroline Barretto
- Institute of Food Safety and Analytical Sciences, Nestlé Research, 1000 Lausanne 26, Switzerland; (C.R.); (A.-C.P.); (C.N.-B.)
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