WeFaceNano: a user-friendly pipeline for complete ONT sequence assembly and detection of antibiotic resistance in multi-plasmid bacterial isolates

Abstract Background Bacterial plasmids often carry antibiotic resistance genes and are a significant factor in the spread of antibiotic resistance. The ability to completely assemble plasmid sequences would facilitate the localization of antibiotic resistance genes, the identification of genes that promote plasmid transmission and the accurate tracking of plasmid mobility. However, the complete assembly of plasmid sequences using the currently most widely used sequencing platform (Illumina-based sequencing) is restricted due to the generation of short sequence lengths. The long-read Oxford Nanopore Technologies (ONT) sequencing platform overcomes this limitation. Still, the assembly of plasmid sequence data remains challenging due to software incompatibility with long-reads and the error rate generated using ONT sequencing. Bioinformatics pipelines have been developed for ONT-generated sequencing but require computational skills that frequently are beyond the abilities of scientific researchers. To overcome this challenge, the authors developed ‘WeFaceNano’, a user-friendly Web interFace for rapid assembly and analysis of plasmid DNA sequences generated using the ONT platform. WeFaceNano includes: a read statistics report; two assemblers (Miniasm and Flye); BLAST searching; the detection of antibiotic resistance- and replicon genes and several plasmid visualizations. A user-friendly interface displays the main features of WeFaceNano and gives access to the analysis tools. Results Publicly available ONT sequence data of 21 plasmids were used to validate WeFaceNano, with plasmid assemblages and anti-microbial resistance gene detection being concordant with the published results. Interestingly, the “Flye” assembler with “meta” settings generated the most complete plasmids. Conclusions WeFaceNano is a user-friendly open-source software pipeline suitable for accurate plasmid assembly and the detection of anti-microbial resistance genes in (clinical) samples where multiple plasmids can be present.

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655. Detection of Antibiotic Resistance Genes in Clinical Samples using T2 Magnetic Resonance

Open Forum Infectious Diseases ◽

10.1093/ofid/ofz360.723 ◽

2019 ◽

Vol 6 (Supplement_2) ◽

pp. S301-S301

Author(s):

Jessica L Snyder ◽

Brendan Manning ◽

Robert Shivers ◽

Daniel Gamero ◽

Heidi Giese ◽

...

Keyword(s):

Antibiotic Resistance ◽

Magnetic Resonance ◽

Species Identification ◽

Resistance Genes ◽

Antibiotic Resistance Genes ◽

Resistance Testing ◽

Clinical Samples ◽

Antibiotic Resistant ◽

Blood Samples ◽

Culture Independent

Abstract Background Antibiotic-resistant bacteria are spread through selective pressure from the use of broad-spectrum empirical therapies, mobile genetic elements that pass resistance genes between species, and the inability to rapidly and appropriately respond to their presence. Resistance gene identification is often performed with post culture molecular diagnostic tests. The T2Resistance Panel, which detects methicillin resistance genes mecA/C; vancomycin resistance genes vanA/B; carbapenemases blaKPC, blaOXA-48,blaNDM, blaVIM, and blaIMP; AmpC β-lactamases blaCMY and blaDHA; and extended-spectrum β-lactamases blaCTX-M directly from patient blood samples, is based on T2 magnetic resonance (T2MR), an FDA-cleared technology with demonstrated high sensitivity and specificity for culture-independent bacterial and fungal species identification. Here we report the clinical performance of T2MR detection of resistance genes directly from patient blood samples. Methods Patients with a clinical diagnosis of sepsis and an order for blood culture (BC) were enrolled in the study at two sites. BCs were managed using standard procedures and MALDI-TOF for species identification. Resistance testing with the T2MR assay was performed on a direct patient draw and compared with diagnostic test results from concurrent BC specimen and BC specimen taken at other points in time. The potential impact on therapy was evaluated through patient chart review. Results T2MR detected the same resistance genes as detected by post culture diagnostics in 100% of samples from concurrent blood draws. Discordant results occurred when T2MR was taken ≥48 hours after BC for patients on antimicrobial therapy. The average time to positive result was 5.9 hours with T2MR vs. 30.6 hours with post-culture molecular testing. Conclusion The T2Resistance Panel detected antibiotic resistance genes in clinical samples and displayed agreement with post culture genetic testing. T2MR results were achieved faster than culture-dependent diagnostic testing results and may allow for an earlier change from empiric to directed therapy. The use of culture-independent diagnostics like T2MR could enable a quicker response to antibiotic-resistant organisms for individual patients and developing outbreaks. Disclosures All authors: No reported disclosures.

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Molecular Analysis of Antibiotic Resistance Gene Clusters in Vibrio cholerae O139 and O1 SXT Constins

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.45.11.2991-3000.2001 ◽

2001 ◽

Vol 45 (11) ◽

pp. 2991-3000 ◽

Cited By ~ 210

Author(s):

Bianca Hochhut ◽

Yasmin Lotfi ◽

Didier Mazel ◽

Shah M. Faruque ◽

Roger Woodgate ◽

...

Keyword(s):

Antibiotic Resistance ◽

Vibrio Cholerae ◽

Resistance Gene ◽

Resistance Genes ◽

Dna Sequences ◽

Antibiotic Resistance Gene ◽

Antibiotic Resistance Genes ◽

Gene Clusters ◽

Vibrio Cholerae O139 ◽

El Tor

ABSTRACT Many recent Asian clinical Vibrio cholerae E1 Tor O1 and O139 isolates are resistant to the antibiotics sulfamethoxazole (Su), trimethoprim (Tm), chloramphenicol (Cm), and streptomycin (Sm). The corresponding resistance genes are located on large conjugative elements (SXT constins) that are integrated into prfC on the V. cholerae chromosome. We determined the DNA sequences of the antibiotic resistance genes in the SXT constin in MO10, an O139 isolate. In SXTMO10, these genes are clustered within a composite transposon-like structure found near the element's 5′ end. The genes conferring resistance to Cm (floR), Su (sulII), and Sm (strA and strB) correspond to previously described genes, whereas the gene conferring resistance to Tm, designated dfr18, is novel. In some other O139 isolates the antibiotic resistance gene cluster was found to be deleted from the SXT-related constin. The El Tor O1 SXT constin, SXTET, does not contain the same resistance genes as SXTMO10. In this constin, the Tm resistance determinant was located nearly 70 kbp away from the other resistance genes and found in a novel type of integron that constitutes a fourth class of resistance integrons. These studies indicate that there is considerable flux in the antibiotic resistance genes found in the SXT family of constins and point to a model for the evolution of these related mobile elements.

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Analysis of virulence factors and antibiotic resistance genes in Group B Streptococcus from clinical samples

10.21203/rs.2.21004/v6 ◽

2020 ◽

Author(s):

Raymond Mudzana ◽

Rooyen T Mavenyengwa ◽

Muchaneta Gudza-Mugabe

Keyword(s):

Antibiotic Resistance ◽

Pregnant Women ◽

Resistance Genes ◽

Virulence Genes ◽

Antimicrobial Agents ◽

Antibiotic Resistance Genes ◽

Penicillin G ◽

Multi Drug Resistance ◽

Clinical Samples ◽

Group B

Abstract Background: Streptococcus agalacticae (Group B Streptococcus, GBS) is one of the most important causative agents of serious infections among neonates. This study was carried out to identify antibiotic resistance and virulence genes associated with GBS isolated from pregnant women.Methods: A total of 43 GBS isolates were obtained from 420 vaginal samples collected from HIV positive and negative women who were 13-35 weeks pregnant attending Antenatal Care at Chitungwiza and Harare Central Hospitals in Zimbabwe. Identification tests of GBS isolates was done using standard bacteriological methods and molecular identification testing. Antibiotic susceptibility testing was done using the modified Kirby-Bauer method and E-test strips. The boiling method was used to extract DNA and Polymerase Chain Reaction (PCR) was used to screen for 13 genes. Data was fed into SPSS 24.0.Results: Nine distinct virulence gene profiles were identified and hly-scpB-bca-rib 37.2% (16/43) was common. The virulence genes identified were namely hly 97.8% (42/43), scpB 90.1% (39/43), bca 86.0% (37/43), rib 69.8% (30/43) and bac 11.6% (5/43). High resistance to tetracycline 97.7% (42/43) was reported followed by 72.1% (31/43) cefazolin, 69.8% (30/43) penicillin G, 58.1% (25/43) ampicillin, 55.8% (24/43) clindamycin, 46.5% (20/43) ceftriaxone, 34.9% (15/43) chloramphenicol, and 30.2% (13/43) for both erythromycin and vancomycin using disk diffusion. Antibiotic resistance genes among the resistant and intermediate-resistant isolates showed high frequencies for tetM 97.6% (41/42) and low frequencies for ermB 34.5% (10/29), ermTR 10.3% (3/29), mefA 3.4% (1/29), tetO 2.4% (1/42) and linB 0% (0/35). The atr housekeeping gene yielded 100% (43/43) positive results, whilst the mobile genetic element IS1548 yielded 9.3% (4/43).Conclusion: The study showed high prevalence of hly, scpB, bca and rib virulence genes in S. agalactiae strains isolated from pregnant women. Tetracycline resistance was predominantly caused by the tetM gene, whilst macrolide resistance was predominantly due to the presence of erm methylase, with the ermB gene being more prevalent. Multi-drug resistance coupled with the recovery of resistant isolates to antimicrobial agents such as penicillins indicates the importance of GBS surveillance and susceptibility tests. It was also observed that in vitro phenotypic resistance is not always accurately predicted by resistance genotypes.

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Role of biofilm-specific antibiotic resistance genes PA0756-0757, PA5033 and PA2070 in Pseudomonas aeruginosa

10.1101/341826 ◽

2018 ◽

Author(s):

Prasanth Manohar ◽

Thamaraiselvan Shanthini ◽

Reethu Ann Philip ◽

Subramani Ramkumar ◽

Manali Kale ◽

...

Keyword(s):

Pseudomonas Aeruginosa ◽

Antibiotic Resistance ◽

Resistance Genes ◽

Biofilm Formation ◽

Tamil Nadu ◽

Antibiotic Resistance Genes ◽

Clinical Samples ◽

Cross Sectional ◽

Antibiotic Resistant ◽

Resistant Genes

AbstractTo evaluate the presence of biofilm-specific antibiotic-resistant genes, PA0756-0757, PA5033 and PA2070 in Pseudomonas aeruginosa isolated from clinical samples in Tamil Nadu. For this cross-sectional study, 24 clinical isolates (included pus, urine, wound, and blood) were collected from two diagnostic centers in Chennai from May 2015 to February 2016. Biofilm formation was assessed using microtiter dish biofilm formation assay and minimal inhibitory concentration (MIC) and minimal bactericidal concentrations (MBC) were determined for planktonic and biofilm cells (MBC assay). Further, PCR amplification of biofilm-specific antibiotic resistance genes PA0756-0757, PA5033 and PA2070 were performed. Biofilm formation was found to be moderate/strong in 16 strains. MBC for planktonic cells showed that 4, 7, 10 and 14 strains were susceptible to gentamicin, ciprofloxacin, meropenem and colistin respectively. In MBC assay for biofilm cells (MBC-B), all the 16 biofilm producing strains were resistant to ciprofloxacin and gentamicin whereas nine and four were resistant to meropenem, and colistin respectively. The biofilm-specific antibiotic-resistant genes PA0756-0757 was found in 10 strains, 6 strains with PA5033 and 9 strains with PA2070 that were found to be resistant phenotypically. This study highlighted the importance of biofilm-specific antibiotic resistance genes PA0756-0757, PA5033, and PA2070 in biofilm-forming P. aeruginosa.

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Detection of antibiotic resistance genes among multiple drug resistant Pseudomonas aeruginosa strains isolated from clinical sources in selected health institutions in Kwara State.

Research Journal of Health Sciences ◽

10.4314/rejhs.v10i1.5 ◽

2021 ◽

Vol 10 (1) ◽

pp. 40-48

Author(s):

O.C. Adekunle ◽

A. Mustapha ◽

G. Odewale ◽

R.O. Ojedele

Keyword(s):

Pseudomonas Aeruginosa ◽

Antibiotic Resistance ◽

Resistance Genes ◽

Multiple Drug Resistance ◽

Antibiotic Resistance Genes ◽

Clinical Samples ◽

Multiple Drug ◽

Antibiotic Resistant ◽

Clinical Specimens ◽

Health Institutions

Introduction: Pseudomonas aeruginosa (P. aeruginosa) is a frequent nosocomial pathogen that causes severe diseases in many clinical and community settings. The objectives were to investigate the occurrence of multiple antibiotic resistant P. aeruginosa strains among clinical samples and to detect the presence of antibiotic resistance genes in the DNA molecules of the strains.Methods: Clinical specimens were collected aseptically from various human anatomical sites in five selected health institutions within Kwara State, Nigeria. Multiple drug resistance patterns of isolated micro-organisms to different antibiotics were determined using the Bauer Kirby disc diffusion technique. The DNA samples of the multiple resistant P. aeruginosa strains were extracted and subjected to Polymerase Chain Reaction (PCR) for resistance gene determination.Results: A total of 145 isolates were identified as P. aeruginosa from the clinical samples. Absolute resistance to ceftazidime, gentamicin and ceftriaxone was observed while low resistance to ciprofloxacin, piperacillin and imipenem was documented. The prevalence of bla VIM , ,bla CTX-M and blaTEM were 34.4 %, 46.7 % and 16.7 % respectively.Conclusion: This study has shown that there is a high occurrence of metallo â-lactamase- producing and antibiotic-resistant strains of P. aeruginosa in clinical specimens from the studied area. Keywords: Metallo â-lactamase enzyme, P. aeruginosa, clinical samples, antibiotic-resistance genes

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Analysis of virulence factors and antibiotic resistance genes in Group B Streptococcus from clinical samples

10.21203/rs.2.21004/v1 ◽

2020 ◽

Author(s):

Raymond Mudzana ◽

Rooyen T Mavenyengwa ◽

Muchaneta Gudza-Mugabe

Keyword(s):

Antibiotic Resistance ◽

Pregnant Women ◽

Virulence Factors ◽

Resistance Genes ◽

Virulence Genes ◽

Group B Streptococcus ◽

Antibiotic Resistance Genes ◽

Virulence Gene ◽

Clinical Samples ◽

Group B

Abstract Background: Streptococcus agalacticae is one of the most important causative agents of serious infections among neonates. Group B Streptococcus (GBS) virulence factors are important in the development of vaccines, whilst antibiotic resistance genes are necessary in understanding the resistance mechanisms used by these pathogens. This study was carried out to identify the virulence genes and antibiotic resistance genes associated with GBS isolated from pregnant women.Methods: A total of 43 GBS isolates were obtained from vaginal samples that were collected from all HIV positive and HIV negative women who were 13-35 weeks pregnant attending Antenatal Care at both Chitungwiza and Harare Central Hospitals in Zimbabwe. Identification tests of GBS isolates was done using standard bacteriological methods including molecular tests. Antibiotic susceptibility testing using 3 antibiotics was done using the modified Kirby-Bauer method. The boiling method was used to extract DNA and Polymerase Chain Reaction (PCR) was used to screen for 13 genes in the isolates. Data was fed into SPSS 24.0 and the Spearman rank correlation test used to determine any correlation among genes.Results: Nine distinct virulence gene profiles were identified. The profiles hly-scpB-bca-rib 37.2% (16/43) and hly-scpB-bca 18.6% (8/43) were common among GBS isolates. The following virulence gene frequencies were obtained namely hly 97.8% (42/43), scpB 90.1% (39/43), bca 86.0% (37/43), rib 69.8% (30/43) and bac 11.6% (5/43). Antibiotic resistance genes showed high frequencies for tetM 97.6% (41/42) and low frequencies for ermB 34.5% (10/29), ermTR 10.3% (3/29), mefA 3.4% (1/29), tetO 2.4% (1/42) and linB 0% (0/35). The atr housekeeping gene amplification yielded 100% (43/43) positive results, whilst the mobile genetic element IS1548 yielded a low 9.3% (4/43).Conclusion: The study showed a high prevalence of multiple virulence genes hly, scpB, bca and rib in S. agalactiae strains isolated from pregnant women. Tetracycline resistance was found to be predominantly caused by the tetM gene, whilst macrolide resistance was predominantly due to the presence of erm methylase, with the ermB gene being more prevalent. It was also observed that in vitro phenotypic resistance is not always accurately predicted by resistance genotypes.

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Appearance of synthetic vector-associated antibiotic resistance genes in next-generation sequences

10.1101/392225 ◽

2018 ◽

Author(s):

George Taiaroa ◽

Gregory M. Cook ◽

Deborah A Williamson

Keyword(s):

Antibiotic Resistance ◽

Resistance Genes ◽

Sequence Data ◽

Antibiotic Resistance Genes ◽

Data Sets ◽

Next Generation ◽

Beta Lactam ◽

Sequence Contigs ◽

Beta Lactam Antibiotics ◽

Genome Shotgun Sequence

SynopsisBackgroundNext-generation sequencing methods have broad application in addressing increasing antibiotic resistance, with identification of antibiotic resistance genes (ARGs) having direct clinical relevance.ObjectivesHere, we describe the appearance of synthetic vector-associated ARGs in major public next-generation sequence data sets and assemblies, including in environmental samples and high priority pathogenic microorganisms.MethodsA search of selected databases – the National Centre for Biotechnology Information (NCBI) nucleotide collection, NCBI whole genome shotgun sequence contigs and literature-associated European Nucleotide Archive (ENA) datasets, was carried out using sequences characteristic of pUC-family synthetic vectors as a query in BLASTn. Identified hits were confirmed as being of synthetic origin, and further explored through alignment and comparison to primary read sets.ResultsSynthetic vectors are attributed to a range of organisms in each of the NCBI databases searched, including examples belonging to each Kingdom of life. These synthetic vectors are associated with various ARGs, primarily those encoding resistance to beta-lactam antibiotics and aminoglycosides. Synthetic vector associated ARGs are also observed in multiple environmental meta-transcriptome datasets, as shown through analysis of associated ENA primary reads, and are proposed to have led to incorrect statements being made in the literature on the abundance of ARGs.ConclusionsAppearance of synthetic vector-associated ARGs can confound the study of antimicrobial resistance in varied settings, and may have clinical implications in the nearfuture.

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Identification of Microbiome Etiology Associated With Drug Resistance in Pleural Empyema

Frontiers in Cellular and Infection Microbiology ◽

10.3389/fcimb.2021.637018 ◽

2021 ◽

Vol 11 ◽

Author(s):

Zhaoyan Chen ◽

Hang Cheng ◽

Zhao Cai ◽

Qingjun Wei ◽

Jinlong Li ◽

...

Keyword(s):

Antibiotic Resistance ◽

Microbial Community ◽

Pleural Effusion ◽

Resistance Genes ◽

Antimicrobial Therapy ◽

Bacterial Species ◽

Antibiotic Resistance Genes ◽

Pleural Empyema ◽

Sequencing Platform ◽

Core Species

Identification of the offending organism and appropriate antimicrobial therapy are crucial for treating empyema. Diagnosis of empyema is largely obscured by the conventional bacterial cultivation and PCR process that has relatively low sensitivity, leading to limited understanding of the etiopathogenesis, microbiology, and role of antibiotics in the pleural cavity. To expand our understanding of its pathophysiology, we have carried out a metagenomic snapshot of the pleural effusion from 45 empyema patients by Illumina sequencing platform to assess its taxonomic, and antibiotic resistome structure. Our results showed that the variation of microbiota in the pleural effusion is generally stratified, not continuous. There are two distinct microbiome clusters observed in the forty-five samples: HA-SA type and LA-SA type. The categorization is mostly driven by species composition: HA-SA type is marked by Staphylococcus aureus as the core species, with other enriched 6 bacteria and 3 fungi, forming a low diversity and highly stable microbial community; whereas the LA-SA type has a more diverse microbial community with a distinct set of bacterial species that are assumed to be the oral origin. The microbial community does not shape the dominant antibiotic resistance classes which were common in the two types, while the increase of microbial diversity was correlated with the increase in antibiotic resistance genes. The existence of well-balanced microbial symbiotic states might respond differently to pathogen colonization and drug intake. This study provides a deeper understanding of the pathobiology of pleural empyema and suggests that potential resistance genes may hinder the antimicrobial therapy of empyema.

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Recovering Escherichia coli Plasmids in the Absence of Long-Read Sequencing Data

Microorganisms ◽

10.3390/microorganisms9081613 ◽

2021 ◽

Vol 9 (8) ◽

pp. 1613

Author(s):

Julian A. Paganini ◽

Nienke L. Plantinga ◽

Sergio Arredondo-Alonso ◽

Rob J. L. Willems ◽

Anita C. Schürch

Keyword(s):

Antibiotic Resistance ◽

Resistance Genes ◽

Antibiotic Resistance Genes ◽

Multidrug Resistant ◽

Special Focus ◽

Valuable Insight ◽

Sequencing Data ◽

Extended Spectrum Beta Lactamase ◽

E Coli ◽

Long Read

The incidence of infections caused by multidrug-resistant E. coli strains has risen in the past years. Antibiotic resistance in E. coli is often mediated by acquisition and maintenance of plasmids. The study of E. coli plasmid epidemiology and genomics often requires long-read sequencing information, but recently a number of tools that allow plasmid prediction from short-read data have been developed. Here, we reviewed 25 available plasmid prediction tools and categorized them into binary plasmid/chromosome classification tools and plasmid reconstruction tools. We benchmarked six tools (MOB-suite, plasmidSPAdes, gplas, FishingForPlasmids, HyAsP and SCAPP) that aim to reliably reconstruct distinct plasmids, with a special focus on plasmids carrying antibiotic resistance genes (ARGs) such as extended-spectrum beta-lactamase genes. We found that two thirds (n = 425, 66.3%) of all plasmids were correctly reconstructed by at least one of the six tools, with a range of 92 (14.58%) to 317 (50.23%) correctly predicted plasmids. However, the majority of plasmids that carried antibiotic resistance genes (n = 85, 57.8%) could not be completely recovered as distinct plasmids by any of the tools. MOB-suite was the only tool that was able to correctly reconstruct the majority of plasmids (n = 317, 50.23%), and performed best at reconstructing large plasmids (n = 166, 46.37%) and ARG-plasmids (n = 41, 27.9%), but predictions frequently contained chromosome contamination (40%). In contrast, plasmidSPAdes reconstructed the highest fraction of plasmids smaller than 18 kbp (n = 168, 61.54%). Large ARG-plasmids, however, were frequently merged with sequences derived from distinct replicons. Available bioinformatic tools can provide valuable insight into E. coli plasmids, but also have important limitations. This work will serve as a guideline for selecting the most appropriate plasmid reconstruction tool for studies focusing on E. coli plasmids in the absence of long-read sequencing data.

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NanoARG: A web service for identification of antimicrobial resistance elements from nanopore-derived environmental metagenomes

10.1101/483248 ◽

2018 ◽

Author(s):

G. A. Arango-Argoty ◽

D. Dai ◽

A. Pruden ◽

P. Vikesland ◽

L. S. Heath ◽

...

Keyword(s):

Antibiotic Resistance ◽

Resistance Genes ◽

Sequence Data ◽

Antibiotic Resistance Genes ◽

Metal Resistance ◽

Direct Selection ◽

Human Pathogens ◽

Next Generation Sequencing Technology ◽

Monitoring Tools ◽

Long Reads

ABSTRACTDirect selection pressures imposed by antibiotics, indirect pressures by co-selective agents, and horizontal gene transfer are fundamental drivers of the evolution and spread of antibiotic resistance. Therefore, effective environmental monitoring tools should ideally capture not only antibiotic resistance genes (ARGs), but also mobile genetic elements (MGEs) and indicators of co-selective forces, such as metal resistance genes (MRGs). Further, a major challenge towards characterizing potential human risk is the ability to identify bacterial host organisms, especially human pathogens. Historically, short reads yielded by next-generation sequencing technology has hampered confidence in assemblies for achieving these purposes. Here we introduce NanoARG, an online computational resource that takes advantage of long reads produced by MinION nanopore sequencing. Specifically, long nanopore reads enable identification of ARGs in the context of relevant neighboring genes, providing relevant insight into mobility, co-selection, and pathogenicity. NanoARG allows users to upload sequence data online and provides various means to analyze and visualize the data, including quantitative and simultaneous profiling of ARG, MRG, MGE, and pathogens. NanoARG is publicly available and freely accessible at http://bench.cs.vt.edu/nanoARG.

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