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  1. Article ; Online: In response to: "Twelve tips for integrating podcasts into medical education".

    Calac, Alec J / Cooper, Ashley M / Krishnamurthy, Sudarshan

    Medical teacher

    2024  , Page(s) 1

    Language English
    Publishing date 2024-01-12
    Publishing country England
    Document type Journal Article
    ZDB-ID 424426-6
    ISSN 1466-187X ; 0142-159X
    ISSN (online) 1466-187X
    ISSN 0142-159X
    DOI 10.1080/0142159X.2023.2299318
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.B 2176: Show issues Location:
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  2. Article ; Online: Finding the missing millions affected by tuberculosis is one thing; treating them is another.

    Cooper, Ashley

    The Lancet. Respiratory medicine

    2019  Volume 7, Issue 9, Page(s) 741

    MeSH term(s) Humans ; India/epidemiology ; Tuberculosis/epidemiology ; Tuberculosis/prevention & control ; Tuberculosis/therapy ; Tuberculosis Vaccines/therapeutic use
    Chemical Substances Tuberculosis Vaccines
    Language English
    Publishing date 2019-06-06
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 2686754-0
    ISSN 2213-2619 ; 2213-2600
    ISSN (online) 2213-2619
    ISSN 2213-2600
    DOI 10.1016/S2213-2600(19)30196-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Rewiring public understanding of neurological disorders.

    Cooper, Ashley

    The Lancet. Neurology

    2018  Volume 19, Issue 1, Page(s) 37

    Language English
    Publishing date 2018-11-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 2081241-3
    ISSN 1474-4465 ; 1474-4422
    ISSN (online) 1474-4465
    ISSN 1474-4422
    DOI 10.1016/S1474-4422(18)30452-6
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5955: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (2.OG)
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  4. Article ; Online: Modeling the limits of detection for antimicrobial resistance genes in agri-food samples: a comparative analysis of bioinformatics tools.

    Cooper, Ashley L / Low, Andrew / Wong, Alex / Tamber, Sandeep / Blais, Burton W / Carrillo, Catherine D

    BMC microbiology

    2024  Volume 24, Issue 1, Page(s) 31

    Abstract: Background: Although the spread of antimicrobial resistance (AMR) through food and its production poses a significant concern, there is limited research on the prevalence of AMR bacteria in various agri-food products. Sequencing technologies are ... ...

    Abstract Background: Although the spread of antimicrobial resistance (AMR) through food and its production poses a significant concern, there is limited research on the prevalence of AMR bacteria in various agri-food products. Sequencing technologies are increasingly being used to track the spread of AMR genes (ARGs) in bacteria, and metagenomics has the potential to bypass some of the limitations of single isolate characterization by allowing simultaneous analysis of the agri-food product microbiome and associated resistome. However, metagenomics may still be hindered by methodological biases, presence of eukaryotic DNA, and difficulties in detecting low abundance targets within an attainable sequence coverage. The goal of this study was to assess whether limits of detection of ARGs in agri-food metagenomes were influenced by sample type and bioinformatic approaches.
    Results: We simulated metagenomes containing different proportions of AMR pathogens and analysed them for taxonomic composition and ARGs using several common bioinformatic tools. Kraken2/Bracken estimates of species abundance were closest to expected values. However, analysis by both Kraken2/Bracken indicated presence of organisms not included in the synthetic metagenomes. Metaphlan3/Metaphlan4 analysis of community composition was more specific but with lower sensitivity than the Kraken2/Bracken analysis. Accurate detection of ARGs dropped drastically below 5X isolate genome coverage. However, it was sometimes possible to detect ARGs and closely related alleles at lower coverage levels if using a lower ARG-target coverage cutoff (< 80%). While KMA and CARD-RGI only predicted presence of expected ARG-targets or closely related gene-alleles, SRST2 (which allows read to map to multiple targets) falsely reported presence of distantly related ARGs at all isolate genome coverage levels. The presence of background microbiota in metagenomes influenced the accuracy of ARG detection by KMA, resulting in mcr-1 detection at 0.1X isolate coverage in the lettuce but not in the beef metagenome.
    Conclusions: This study demonstrates accurate detection of ARGs in synthetic metagenomes using various bioinformatic methods, provided that reads from the ARG-encoding organism exceed approximately 5X isolate coverage (i.e. 0.4% of a 40 million read metagenome). While lowering thresholds for target gene detection improved sensitivity, this led to the identification of alternative ARG-alleles, potentially confounding the identification of critical ARGs in the resistome. Further advancements in sequencing technologies providing increased coverage depth or extended read lengths may improve ARG detection in agri-food metagenomic samples, enabling use of this approach for tracking clinically important ARGs in agri-food samples.
    MeSH term(s) Animals ; Cattle ; Anti-Bacterial Agents/pharmacology ; Drug Resistance, Bacterial/genetics ; Limit of Detection ; Bacteria/genetics ; Genes, Bacterial/genetics ; Metagenome ; Metagenomics/methods ; Computational Biology
    Chemical Substances Anti-Bacterial Agents
    Language English
    Publishing date 2024-01-20
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041505-9
    ISSN 1471-2180 ; 1471-2180
    ISSN (online) 1471-2180
    ISSN 1471-2180
    DOI 10.1186/s12866-023-03148-6
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Arts Participation Amongst Healthcare Professionals: An Analysis of US Census Data.

    Cooper, Ashley M / Zhong, Anthony / Jain, Bhav / Wong, Lisa / Jones, David S

    Journal of general internal medicine

    2024  

    Language English
    Publishing date 2024-03-26
    Publishing country United States
    Document type Letter
    ZDB-ID 639008-0
    ISSN 1525-1497 ; 0884-8734
    ISSN (online) 1525-1497
    ISSN 0884-8734
    DOI 10.1007/s11606-024-08711-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Analysis of Antimicrobial Resistance in Bacterial Pathogens Recovered from Food and Human Sources: Insights from 639,087 Bacterial Whole-Genome Sequences in the NCBI Pathogen Detection Database.

    Cooper, Ashley L / Wong, Alex / Tamber, Sandeep / Blais, Burton W / Carrillo, Catherine D

    Microorganisms

    2024  Volume 12, Issue 4

    Abstract: Understanding the role of foods in the emergence and spread of antimicrobial resistance necessitates the initial documentation of antibiotic resistance genes within bacterial species found in foods. Here, the NCBI Pathogen Detection database was used to ... ...

    Abstract Understanding the role of foods in the emergence and spread of antimicrobial resistance necessitates the initial documentation of antibiotic resistance genes within bacterial species found in foods. Here, the NCBI Pathogen Detection database was used to query antimicrobial resistance gene prevalence in foodborne and human clinical bacterial isolates. Of the 1,843,630 sequence entries, 639,087 (34.7%) were assigned to foodborne or human clinical sources with 147,788 (23.14%) from food and 427,614 (76.88%) from humans. The majority of foodborne isolates were either
    Language English
    Publishing date 2024-03-30
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2720891-6
    ISSN 2076-2607
    ISSN 2076-2607
    DOI 10.3390/microorganisms12040709
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Genomically Informed Custom Selective Enrichment of Shiga Toxigenic Escherichia coli (STEC) Outbreak Strains in Foods Using Antibiotics.

    Tapp, Kyle / Deschênes, Mylène / Cooper, Ashley / Carrillo, Catherine / Blais, Burton

    Journal of food protection

    2023  Volume 86, Issue 3, Page(s) 100052

    Abstract: Shiga toxigenic Escherichia coli (STEC) have been implicated in major foodborne outbreaks worldwide. The STEC family of pathogens is biochemically diverse, and current microbiological methods for detecting STEC are limited by the lack of a universal ... ...

    Abstract Shiga toxigenic Escherichia coli (STEC) have been implicated in major foodborne outbreaks worldwide. The STEC family of pathogens is biochemically diverse, and current microbiological methods for detecting STEC are limited by the lack of a universal selective enrichment approach and prone to interference by high levels of background microbiota associated with certain types of foods. A novel approach has been developed for the recovery of foodborne illness outbreak strains during outbreak investigations based on the analysis of whole genome sequence data of implicated clinical isolates to determine antimicrobial resistance (AMR) genes. The presence of certain AMR genes in STEC has been correlated with the ability to grow in the presence of a specific antibiotic, which can be used to supplement enrichment broths to improve the recovery of a target strain. The enhanced recovery of STEC strains with different AMR profiles from various food types (beef, sprouts, leafy greens, and raw milk cheese) containing high levels of background microbiota was demonstrated using AMR predictions for nine different antibiotics. This genomically informed custom selective enrichment approach increases the availability of analytical options and improves the reliability of food microbiological analyses in confirming food vehicles implicated in outbreak events and defining the scope of product contamination to support risk assessment and risk management actions.
    MeSH term(s) Animals ; Cattle ; Humans ; Shiga-Toxigenic Escherichia coli ; Escherichia coli Infections/microbiology ; Anti-Bacterial Agents/pharmacology ; Reproducibility of Results ; Disease Outbreaks ; Food Microbiology
    Chemical Substances Anti-Bacterial Agents
    Language English
    Publishing date 2023-01-26
    Publishing country United States
    Document type Journal Article
    ZDB-ID 243284-5
    ISSN 1944-9097 ; 0362-028X
    ISSN (online) 1944-9097
    ISSN 0362-028X
    DOI 10.1016/j.jfp.2023.100052
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Bonn / Germany

    Z 2631: Show issues

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  8. Article ; Online: Genomically Informed Custom Selective Enrichment of Shiga Toxigenic Escherichia coli (STEC) Outbreak Strains in Foods Using Antibiotics

    Tapp, Kyle / Deschênes, Mylène / Cooper, Ashley / Carrillo, Catherine / Blais, Burton

    Journal of Food Protection. 2023 Mar., v. 86, no. 3 p.100052-

    2023  

    Abstract: Shiga toxigenic Escherichia coli (STEC) have been implicated in major foodborne outbreaks worldwide. The STEC family of pathogens is biochemically diverse, and current microbiological methods for detecting STEC are limited by the lack of a universal ... ...

    Abstract Shiga toxigenic Escherichia coli (STEC) have been implicated in major foodborne outbreaks worldwide. The STEC family of pathogens is biochemically diverse, and current microbiological methods for detecting STEC are limited by the lack of a universal selective enrichment approach and prone to interference by high levels of background microbiota associated with certain types of foods. A novel approach has been developed for the recovery of foodborne illness outbreak strains during outbreak investigations based on the analysis of whole genome sequence data of implicated clinical isolates to determine antimicrobial resistance (AMR) genes. The presence of certain AMR genes in STEC has been correlated with the ability to grow in the presence of a specific antibiotic, which can be used to supplement enrichment broths to improve the recovery of a target strain. The enhanced recovery of STEC strains with different AMR profiles from various food types (beef, sprouts, leafy greens, and raw milk cheese) containing high levels of background microbiota was demonstrated using AMR predictions for nine different antibiotics. This genomically informed custom selective enrichment approach increases the availability of analytical options and improves the reliability of food microbiological analyses in confirming food vehicles implicated in outbreak events and defining the scope of product contamination to support risk assessment and risk management actions.
    Keywords Shiga toxin-producing Escherichia coli ; antibiotic resistance ; antibiotics ; beef ; cheeses ; food safety ; foodborne illness ; microorganisms ; nucleotide sequences ; raw milk ; risk assessment ; risk management ; sequence analysis ; Custom selective enrichment ; Shiga toxigenic E. coli ; Strain specific ; STEC ; AMR
    Language English
    Dates of publication 2023-03
    Publishing place Elsevier Inc.
    Document type Article ; Online
    Note Use and reproduction
    ZDB-ID 243284-5
    ISSN 1944-9097 ; 0362-028X
    ISSN (online) 1944-9097
    ISSN 0362-028X
    DOI 10.1016/j.jfp.2023.100052
    Database NAL-Catalogue (AGRICOLA)

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  9. Article ; Online: A Girl with Limp and Rash on the Palms and Soles.

    Kesh, Susamita / Ward, Jacob S / Cooper, Ashley M

    Pediatrics in review

    2021  Volume 42, Issue Suppl 2, Page(s) 99–103

    MeSH term(s) Exanthema/etiology ; Female ; Gait ; Hand ; Humans
    Language English
    Publishing date 2021-09-01
    Publishing country United States
    Document type Journal Article
    ZDB-ID 774515-1
    ISSN 1526-3347 ; 0191-9601
    ISSN (online) 1526-3347
    ISSN 0191-9601
    DOI 10.1542/pir.2018-0226
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Targeted metagenomics using bait-capture to detect antibiotic resistance genes in retail meat and seafood.

    Flint, Annika / Cooper, Ashley / Rao, Mary / Weedmark, Kelly / Carrillo, Catherine / Tamber, Sandeep

    Frontiers in microbiology

    2023  Volume 14, Page(s) 1188872

    Abstract: Metagenomics analysis of foods has the potential to provide comprehensive data on the presence and prevalence of antimicrobial resistance (AMR) genes in the microbiome of foods. However, AMR genes are generally present in low abundance compared to other ... ...

    Abstract Metagenomics analysis of foods has the potential to provide comprehensive data on the presence and prevalence of antimicrobial resistance (AMR) genes in the microbiome of foods. However, AMR genes are generally present in low abundance compared to other bacterial genes in the food microbiome and consequently require multiple rounds of in-depth sequencing for detection. Here, a metagenomics approach, using bait-capture probes targeting antimicrobial resistance and plasmid genes, is used to characterize the resistome and plasmidome of retail beef, chicken, oyster, shrimp, and veal enrichment cultures (
    Language English
    Publishing date 2023-07-13
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2587354-4
    ISSN 1664-302X
    ISSN 1664-302X
    DOI 10.3389/fmicb.2023.1188872
    Database MEDical Literature Analysis and Retrieval System OnLINE

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