scholarly journals Benchmarking software to predict antibiotic resistance phenotypes in shotgun metagenomes using simulated data

2022 ◽  
Author(s):  
Emily F Wissel ◽  
Brooke M Talbot ◽  
Bjorn A Johnson ◽  
Robert A Petit ◽  
Vicki Hertzberg ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Open Source ◽  
Simulated Data ◽  
Metagenomic Data ◽  
Clinical Samples ◽  
Bacterial Strains ◽  
Minimal Processing ◽  
Genotypic Resistance ◽  
Shotgun Metagenomics ◽  
Bioinformatic Tools

The use of shotgun metagenomics for AMR detection is appealing because data can be generated from clinical samples with minimal processing. Detecting antimicrobial resistance (AMR) in clinical genomic data is an important epidemiological task, yet a complex bioinformatic process. Many software tools exist to detect AMR genes, but they have mostly been tested in their detection of genotypic resistance in individual bacterial strains. It is important to understand how well these bioinformatic tools detect AMR genes in shotgun metagenomic data. We developed a software pipeline, hAMRoaster (https://github.com/ewissel/hAMRoaster), for assessing accuracy of prediction of antibiotic resistance phenotypes. For evaluation purposes, we simulated a short read (Illumina) shotgun metagenomics community of eight bacterial pathogens with extensive antibiotic susceptibility testing profiles. We benchmarked nine open source bioinformatics tools for detecting AMR genes that 1) were conda or Docker installable, 2) had been actively maintained, 3) had an open source license, and 4) took FASTA or FASTQ files as input. Several metrics were calculated for each tool including sensitivity, specificity, and F1 at three coverage levels. This study revealed that tools were highly variable in sensitivity (0.25 - 0.99) and specificity (0.2 - 1) in detection of resistance in our synthetic FASTQ files despite similar databases and methods implemented. Tools performed similarly at all coverage levels (5x, 50x, 100x). Cohen’s kappa revealed low agreement across tools.

scholarly journals The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples

2019 ◽  
Author(s):  
H. Soon Gweon ◽  
Liam P. Shaw ◽  
Jeremy Swann ◽  
Nicola De Maio ◽  
Manal AbuOun ◽  
...  
Keyword(s):  
Data Processing ◽  
Open Source ◽  
Open Source Software ◽  
River Sediment ◽  
Taxonomic Composition ◽  
Sequencing Depth ◽  
Gene Content ◽  
Metagenomic Data ◽  
Software Pipeline ◽  
Shotgun Metagenomics

ABSTRACTBackgroundShotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (∼200 million reads per sample). Alongside this, we cultured single-colony isolates ofEnterobacteriaceaefrom the same samples and used hybrid sequencing (short- and long-reads) to create high-quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open-source software pipeline, ‘ResPipe’.ResultsTaxonomic profiling was much more stable to sequencing depth than AMR gene content. 1 million reads per sample was sufficient to achieve <1% dissimilarity to the full taxonomic composition. However, at least 80 million reads per sample were required to recover the full richness of different AMR gene families present in the sample, and additional allelic diversity of AMR genes was still being discovered in effluent at 200 million reads per sample. Normalising the number of reads mapping to AMR genes using gene length and an exogenous spike ofThermus thermophilusDNA substantially changed the estimated gene abundance distributions. While the majority of genomic content from cultured isolates from effluent was recoverable using shotgun metagenomics, this was not the case for pig caeca or river sediment.ConclusionsSequencing depth and profiling method can critically affect the profiling of polymicrobial animal and environmental samples with shotgun metagenomics. Both sequencing of cultured isolates and shotgun metagenomics can recover substantial diversity that is not identified using the other methods. Particular consideration is required when inferring AMR gene content or presence by mapping metagenomic reads to a database. ResPipe, the open-source software pipeline we have developed, is freely available (https://gitlab.com/hsgweon/ResPipe).

scholarly journals The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
H. Soon Gweon ◽  
◽  
Liam P. Shaw ◽  
Jeremy Swann ◽  
Nicola De Maio ◽  
...  
Keyword(s):  
Data Processing ◽  
Open Source ◽  
Open Source Software ◽  
River Sediment ◽  
Taxonomic Composition ◽  
Sequencing Depth ◽  
Gene Content ◽  
Metagenomic Data ◽  
Software Pipeline ◽  
Shotgun Metagenomics

Abstract Background Shotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (~ 200 million reads per sample). Alongside this, we cultured single-colony isolates of Enterobacteriaceae from the same samples and used hybrid sequencing (short- and long-reads) to create high-quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open-source software pipeline, ‘ResPipe’. Results Taxonomic profiling was much more stable to sequencing depth than AMR gene content. 1 million reads per sample was sufficient to achieve < 1% dissimilarity to the full taxonomic composition. However, at least 80 million reads per sample were required to recover the full richness of different AMR gene families present in the sample, and additional allelic diversity of AMR genes was still being discovered in effluent at 200 million reads per sample. Normalising the number of reads mapping to AMR genes using gene length and an exogenous spike of Thermus thermophilus DNA substantially changed the estimated gene abundance distributions. While the majority of genomic content from cultured isolates from effluent was recoverable using shotgun metagenomics, this was not the case for pig caeca or river sediment. Conclusions Sequencing depth and profiling method can critically affect the profiling of polymicrobial animal and environmental samples with shotgun metagenomics. Both sequencing of cultured isolates and shotgun metagenomics can recover substantial diversity that is not identified using the other methods. Particular consideration is required when inferring AMR gene content or presence by mapping metagenomic reads to a database. ResPipe, the open-source software pipeline we have developed, is freely available (https://gitlab.com/hsgweon/ResPipe).

Evaluation of antibacterial potential of various plant extracts against clinically important skin infectious bacterial strains

2020 ◽  
Vol 18 ◽  
Author(s):  
Syeda Kahkashan Kazmi ◽  
Naheed Kauser ◽  
Ayisha Aman ◽  
Aqsa Idrees ◽  
Rashida Rahmat Zohra ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Plant Extracts ◽  
Skin Diseases ◽  
Curcuma Longa ◽  
Diffusion Method ◽  
Clinical Samples ◽  
Santalum Album ◽  
Bacterial Strains ◽  
Citrus Peel ◽  
Antibacterial Potential

Background: At the present time skin problems need to address seriously, antibiotic resistance development is very fast in skin infectious bacteria. For the prevention of all types of skin infections, natural plant extracts can provide suitable defense line because they contain active compounds. Wrinkles, sunburn, itching, black heads, white heads and uneven tone of the skin are the collective issues related to skin. Extensive use of antibiotics for skin diseases is restricted due to the development of worse antibiotic resistance. Objective: In this study the antibacterial potential of plant extracts was assessed against skin infectious bacteria to get alternative cure of skin diseases. Method: Staphylococcus aureus, Staphylococcus epidermidis strains were isolated from clinical samples and E.coli was used as non-pathogenic control strain from Jinnah University for Women strain repository. Their antibacterial activity was performed against eight plant extracts through well diffusion method. Result: Among eight plant extracts, Neem (Azadirachta indica), Turmeric (Curcuma longa), Sandalwood (Santalum album), Shahtara (Fumaria parviflora) Chirayata (Swertia chirayita) and commercially available mixed Citrus peel showed good inhibition of bacterial growth. Discussion: Natural sources such as fruits, herbs, minerals, leaves, flowers, roots, honey and rose water are now becoming part of skin care and treatment products because they possess antimicrobial activities. Skin products with herbal ingredients are now evolving as suitable solutions to the existing skin problems.

BacARscan: A Comprehensive and Interactive Web-Resource to Discern Antibiotic Resistance Gene Diversity in –Omics Datasets

2021 ◽  
Author(s):  
Deeksha Pandey ◽  
Bandana Kumari ◽  
Neelja Singhal ◽  
Manish Kumar
Keyword(s):  
Antibiotic Resistance ◽  
Gene Diversity ◽  
Antibiotic Resistance Gene ◽  
Resistance Mechanism ◽  
Antibiotic Resistance Genes ◽  
Metagenomic Data ◽  
Clinical Samples ◽  
Antibiotics Resistance ◽  
Web Resource ◽  
Proteomic Data

Abstract Regular surveillance of antibiotic resistance genes (ARGs) is important to understand the emergence and epidemiology of antibiotic resistance (AR) in clinical and environmental niches. With diminishing costs, NGS technologies are anticipated to replace classical microbiological and molecular methods for determination of AR. One major hindrance underlying identification and annotation of ARGs from WGS data is that a major part of genome databases contain fragmented genes/genomes (due to incomplete assembly). Herein, we propose a web resource of Bacterial ARGs, named as BacARscan (Bacterial Antibiotic Resistance scan), to detect, predict and characterize ARGs in metagenomic, genomic and proteomic data. The current version of BacARscan comprises 254 ARG models, each annotated with a resistant profile against different classes of antibiotics, resistance mechanism etc. Benchmarking on a combined dataset of AR and non-AR proteins found 92% precision & 95% F-measure. BacARscan can also discriminate between the protein families that are homologous but not all families are involved in the AR. BacARscan identified more ARGs in (a) gut microbiome and (b) datasets comprising short read genomic and proteomic sequences of ESKAPE pathogens. Analysis of clinical metagenomic data indicated its potential to complement and/or supplement WGS based identification of ARGs in clinical samples. BacARscan standalone software and web-server are freely available at http://proteininformatics.org/mkumar/bacarscan and github repository (https://github.com/University-of-Delhi-south-campus/BacARscan).

scholarly journals Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kazutoshi Yoshitake ◽  
Gaku Kimura ◽  
Tomoko Sakami ◽  
Tsuyoshi Watanabe ◽  
Yukiko Taniuchi ◽  
...  
Keyword(s):  
Time Series ◽  
Microbial Communities ◽  
Pacific Coast ◽  
Three Dimensional ◽  
Amplicon Sequencing ◽  
Metagenomic Data ◽  
Shotgun Metagenomics ◽  
Functional Features ◽  
Pacific Coast Of Japan ◽  
Marine Microbial Communities

AbstractAlthough numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.

scholarly journals Mutation-Based Antibiotic Resistance Mechanism in Methicillin-Resistant Staphylococcus aureus Clinical Isolates

2021 ◽  
Vol 14 (5) ◽  
pp. 420
Author(s):  
Tanveer Ali ◽  
Abdul Basit ◽  
Asad Mustafa Karim ◽  
Jung-Hun Lee ◽  
Jeong-Ho Jeon ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Antibiotic Resistance ◽  
Active Site ◽  
Methicillin Resistant Staphylococcus Aureus ◽  
Meca Gene ◽  
Resistance Mechanism ◽  
Ligand Docking ◽  
Clinical Samples ◽  
Allosteric Site ◽  
Methicillin Resistant

β-Lactam antibiotics target penicillin-binding proteins and inhibit the synthesis of peptidoglycan, a crucial step in cell wall biosynthesis. Staphylococcus aureus acquires resistance against β-lactam antibiotics by producing a penicillin-binding protein 2a (PBP2a), encoded by the mecA gene. PBP2a participates in peptidoglycan biosynthesis and exhibits a poor affinity towards β-lactam antibiotics. The current study was performed to determine the diversity and the role of missense mutations of PBP2a in the antibiotic resistance mechanism. The methicillin-resistant Staphylococcus aureus (MRSA) isolates from clinical samples were identified using phenotypic and genotypic techniques. The highest frequency (60%, 18 out of 30) of MRSA was observed in wound specimens. Sequence variation analysis of the mecA gene showed four amino acid substitutions (i.e., E239K, E239R, G246E, and E447K). The E239R mutation was found to be novel. The protein-ligand docking results showed that the E239R mutation in the allosteric site of PBP2a induces conformational changes in the active site and, thus, hinders its interaction with cefoxitin. Therefore, the present report indicates that mutation in the allosteric site of PBP2a provides a more closed active site conformation than wide-type PBP2a and then causes the high-level resistance to cefoxitin.

scholarly journals Microbiota and Metabolomic Patterns in the Breast Milk of Subjects with Celiac Disease on a Gluten-Free Diet

Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2243
Author(s):  
Katherine L. Olshan ◽  
Ali R. Zomorrodi ◽  
Meritxell Pujolassos ◽  
Jacopo Troisi ◽  
Nayeim Khan ◽  
...  
Keyword(s):  
Celiac Disease ◽  
Breast Milk ◽  
Milk Composition ◽  
Gluten Free Diet ◽  
Intestinal Microbiome ◽  
Healthy Controls ◽  
Gluten Free ◽  
Bacterial Strains ◽  
Shotgun Metagenomics ◽  
Functional Pathways

The intestinal microbiome may trigger celiac disease (CD) in individuals with a genetic disposition when exposed to dietary gluten. Research demonstrates that nutrition during infancy is crucial to the intestinal microbiome engraftment. Very few studies to date have focused on the breast milk composition of subjects with a history of CD on a gluten-free diet. Here, we utilize a multi-omics approach with shotgun metagenomics to analyze the breast milk microbiome integrated with metabolome profiling of 36 subjects, 20 with CD on a gluten-free diet and 16 healthy controls. These analyses identified significant differences in bacterial and viral species/strains and functional pathways but no difference in metabolite abundance. Specifically, three bacterial strains with increased abundance were identified in subjects with CD on a gluten-free diet of which one (Rothia mucilaginosa) has been previously linked to autoimmune conditions. We also identified five pathways with increased abundance in subjects with CD on a gluten-free diet. We additionally found four bacterial and two viral species/strains with increased abundance in healthy controls. Overall, the differences observed in bacterial and viral species/strains and in functional pathways observed in our analysis may influence microbiome engraftment in neonates, which may impact their future clinical outcomes.

scholarly journals Antibacterial Compounds from Mushrooms: A Lead to Fight ESKAPEE Pathogenic Bacteria?

Planta Medica ◽  
2020 ◽  
Author(s):  
Violette Hamers ◽  
Clément Huguet ◽  
Mélanie Bourjot ◽  
Aurélie Urbain
Keyword(s):  
Antibiotic Resistance ◽  
Global Health ◽  
Pathogenic Bacteria ◽  
Resistance Mechanisms ◽  
Pathogenic Microorganisms ◽  
Bacterial Strains ◽  
Antibacterial Compounds ◽  
New Antibiotics ◽  
Hospital Stays ◽  
Antibacterial Potential

AbstractInfectious diseases are among the greatest threats to global health in the 21st century, and one critical concern is due to antibiotic resistance developed by an increasing number of bacterial strains. New resistance mechanisms are emerging with many infections becoming more and more difficult if not impossible to treat. This growing phenomenon not only is associated with increased mortality but also with longer hospital stays and higher medical costs. For these reasons, there is an urgent need to find new antibiotics targeting pathogenic microorganisms such as ESKAPEE bacteria. Most of currently approved antibiotics are derived from microorganisms, but higher fungi could constitute an alternative and remarkable reservoir of anti-infectious compounds. For instance, pleuromutilins constitute the first class of antibiotics derived from mushrooms. However, macromycetes still represent a largely unexplored source. Publications reporting the antibacterial potential of mushroom extracts are emerging, but few purified compounds have been evaluated for their bioactivity on pathogenic bacterial strains. Therefore, the aim of this review is to compile up-to-date data about natural products isolated from fruiting body fungi, which significantly inhibit the growth of ESKAPEE pathogenic bacteria. When available, data regarding modes of action and cytotoxicity, mandatory when considering a possible drug development, have been discussed in order to highlight the most promising compounds.

Characterization, Pathogenicity, Phylogeny, and Comparative Genomic Analysis of Pseudomonas tolaasii Strains Isolated from Various Mushrooms in China

2021 ◽  
Author(s):  
Zhenghui Liu ◽  
Yitong Zhao ◽  
Frederick Leo Sossah ◽  
Benjamin Azu Okorley ◽  
Daniel G. Amoako ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Genomic Analysis ◽  
Gene Families ◽  
Effective Control ◽  
Economic Losses ◽  
Comparative Genomic ◽  
Bacterial Strains ◽  
Secretion Systems ◽  
Pseudomonas Tolaasii ◽  
Antimicrobial Resistance Genes

Since 2016, devastating bacterial blotch affecting the fruiting bodies of Agaricus bisporus, Cordyceps militaris, Flammulina filiformis, and Pleurotus ostreatus in China has caused severe economic losses. We isolated 102 bacterial strains and characterized them polyphasically. We identified the causal agent as Pseudomonas tolaasii and confirmed the pathogenicity of the strains. A host range test further confirmed the pathogen’s ability to infect multiple hosts. This is the first report in China of bacterial blotch in C. militaris caused by P. tolaasii. Whole-genome sequences were generated for three strains: Pt11 (6.48 Mb), Pt51 (6.63 Mb), and Pt53 (6.80 Mb), and pangenome analysis was performed with 13 other publicly accessible P. tolaasii genomes to determine their genetic diversity, virulence, antibiotic resistance, and mobile genetic elements. The pangenome of P. tolaasii is open, and many more gene families are likely to emerge with further genome sequencing. Multilocus sequence analysis using the sequences of four common housekeeping genes (glns, gyrB, rpoB, and rpoD) showed high genetic variability among the P. tolaasii strains, with 115 strains clustered into a monophyletic group. The P. tolaasii strains possess various genes for secretion systems, virulence factors, carbohydrate-active enzymes, toxins, secondary metabolites, and antimicrobial resistance genes that are associated with pathogenesis and adapted to different environments. The myriad of insertion sequences, integrons, prophages, and genome islands encoded in the strains may contribute to genome plasticity, virulence, and antibiotic resistance. These findings advance understanding of the determinants of virulence, which can be targeted for the effective control of bacterial blotch disease.

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