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Enterobacteriaceae

Enterobacteriaceae: A large family of Gram-negative bacteria that includes many medically important species, such as Escherichia, Salmonella, Shigella, and Klebsiella.
These pathogens can cause a wide range of infections, from gastroenteritis to urinary tract infections and sepsis.
Researchers studying Enterobacteriaceae can optimize their work through AI-driven protocol comparisons using PubCompare.ai, a innovative platform that helps locate the best protocols from literature, pre-prints, and patents, and enhance reproducibility.
This streamlines the research process and supports data-driven decision making.

Most cited protocols related to «Enterobacteriaceae»

1
Benchmarking Metagenomic Classifiers with Synthetic and Real-World Datasets
The HiSeq and MiSeq metagenomes were built using 20 sets of bacterial whole-genome shotgun reads. These reads were found either as part of the GAGE-B project [21 (link)] or in the NCBI Sequence Read Archive. Each metagenome contains sequences from ten genomes (Additional file 1: Table S1). For both the 10,000 and 10 million read samples of each of these metagenomes, 10% of their sequences were selected from each of the ten component genome data sets (i.e., each genome had equal sequence abundance). All sequences were trimmed to remove low quality bases and adapter sequences.
The composition of these two metagenomes poses certain challenges to our classifiers. For example, Pelosinus fermentans, found in our HiSeq metagenome, cannot be correctly identified at the genus level by Kraken (or any of the other previously described classifiers), because there are no Pelosinus genomes in the RefSeq complete genomes database; however, there are seven such genomes in Kraken-GB’s database, including six strains of P. fermentans. Similarly, in our MiSeq metagenome, Proteus vulgaris is often classified incorrectly at the genus level because the only Proteus genome in Kraken’s database is a single Proteus mirabilis genome. Five more Proteus genomes are present in Kraken-GB’s database, allowing Kraken-GB to classify reads better from that genus. In addition, the MiSeq metagenome contains five genomes from the Enterobacteriaceae family (Citrobacter, Enterobacter, Klebsiella, Proteus and Salmonella). The high sequence similarity between the genera in this family can make distinguishing between genera difficult for any classifier.
The simBA-5 metagenome was created by simulating reads from the set of complete bacterial and archaeal genomes in RefSeq. Replicons from those genomes were used if they were associated with a taxon that had an entry associated with the genus rank, resulting in a set of replicons from 607 genera. We then used the Mason read simulator [22 ] with its Illumina model to produce 10 million 100-bp reads from these genomes. First we created simulated genomes for each species, using a SNP rate of 0.1% and an indel rate of 0.1% (both default parameters), from which we generated the reads. For the simulated reads, we multiplied the default mismatch and indel rates by five, resulting in an average mismatch rate of 2% (ranging from 1% at the beginning of reads to 6% at the ends) and an indel rate of 1% (0.5% insertion probability and 0.5% deletion probability). For the simBA-5 metagenome, the 10,000 read set was generated from a random sample of the 10 million read set.
Wood D.E, & Salzberg S.L. (2014). Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biology, 15(3), R46.
Publication 2014
Bacteria Citrobacter Deletion Mutation Enterobacter Enterobacteriaceae Genome Genome, Archaeal Genome, Bacterial Genome Components INDEL Mutation Klebsiella Metagenome Pelosinus fermentans Proteus Proteus mirabilis Proteus vulgaris Replicon Salmonella Strains
2
Predicting Plasmid Replicons using PlasmidFinder
To predict plasmid replicons using PlasmidFinder (25 (link)) we uploaded assembled sequences (filtered by length—as described above) to the PlasmidFinder webserver (https://cge.cbs.dtu.dk/services/PlasmidFinder/) and ran the computation selecting all available databases (Enterobacteriaceae and Enterecoccus, Streptococcus, Staphylococcus). The %ID threshold was set at 80% and ‘Assembled Genome/Contigs’ was chosen as the type of read. Results were downloaded as raw text files.
Krawczyk P.S., Lipinski L, & Dziembowski A. (2018). PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures. Nucleic Acids Research, 46(6), e35.
Publication 2018
Enterobacteriaceae Genome Plasmids Replicon Staphylococcus Streptococcus
3
Expansion of Plasmid Sequence Database
The MOB-suite v. 1 database contains 12 091 complete plasmids, and due to the increased number of plasmid sequences made available since the original publication, we expanded the database using new data from the NCBI utilizing the same approach described in the supplementary materials of the MOB-suite paper [14 (link)]. The NCBI Entrez nucleotide database was queried in November 2019 with the query ‘plasmid’ AND ‘complete sequence’ AND ‘bacteria [organism]’. The results were then filtered for sequences between 1500 to 400 000 bp in length, with ‘plasmid’ as the genetic compartment and limited to the INSDC (International Nucleotide Sequence Database Collaboration). This yielded an initial set of 33 875 sequences that were then typed using MOB-typer v. 2.1.0 (Table S1, available with the online version of this article). Records were excluded due to the presence of any of the following terms in the title or description: gene, cds, protein, transposon, insertion, protein, region, operon, pseudogene, integrase, transposase, integron, partial, shotgun. The remaining set of 23 280 sequences was then merged with the MOB-suite v.1 database plasmids, which were then de-duplicated by clustering plasmids that had a Mash v. 2.2.2 [17 (link)] distance of 0 and selecting a single representative for subsequent analyses (Table S2). A priority was given to those plasmids that were part of the initial construction of the MOB-suite clusters, which resulted in a total of 17 779 records. The database exhibits a strong bias towards plasmids from Enterobacteriaceae (35 %) as shown in a Krona plot of the plasmid dataset taxonomic composition (Fig. S1). This has the consequence that the threshold optimization may not be fully representative of the underrepresented taxonomic groups.
Robertson J., Bessonov K., Schonfeld J, & Nash J.H. (2020). Universal whole-sequence-based plasmid typing and its utility to prediction of host range and epidemiological surveillance. Microbial Genomics, 6(10), mgen000435.
Publication 2020
Bacteria Base Sequence BP 400 Enterobacteriaceae Genes Integrase Integrons Jumping Genes Nucleotides Operon Plasmids Proteins Pseudogenes Reproduction Transposase
4
Validation of Carbapenemase Identification Method
For validation of the CIM, a selection of 30 Gram-negative isolates was used. This selection included isolates obtained from different institutes across the world carrying known carbapenemase encoding genes and carbapenem susceptible isolates, according to the submitter (Table 1). In addition, 694 isolates submitted to the National Institute for Public Health and the Environment for the national surveillance of carbapenemase-producing Enterobacteriaceae (CPE) by Dutch medical microbiology laboratories (MMLs) during the first six months of 2012 and the first six months of 2013 were used. For the national surveillance of CPE in the Netherlands, Dutch MMLs are requested to submit Enterobacteriaceae isolates with an MIC for meropenem > 0.25 μg/ml. However, more than half of the isolates (411/694, 59%) sent in for CPE surveillance were non-fermenting Gram-negatives belonging to the genera Pseudomonas and Acinetobacter. Furthermore, 35% of the isolates had MICs below 0.25 μg/ml. Nevertheless, all isolates were included in this study.
The species identification, as performed by the MMLs, was confirmed using MALDI-TOF (Bruker Daltonics GmbH, Bremen, Germany) and the MIC for all isolates was confirmed by E-test (BioMerieux Inc., Marcy L’Etoile, France). Culturing of isolates was done on Columbia Sheep Blood (bioTRADING Benelux BV, Mijdrecht, The Netherlands) and Mueller-Hinton agarplates (Oxoid Ltd, Hampshire, United Kingdom). An overview of all CPE surveillance isolates and their characteristics is displayed in Tables 2 and 3.
van der Zwaluw K., de Haan A., Pluister G.N., Bootsma H.J., de Neeling A.J, & Schouls L.M. (2015). The Carbapenem Inactivation Method (CIM), a Simple and Low-Cost Alternative for the Carba NP Test to Assess Phenotypic Carbapenemase Activity in Gram-Negative Rods. PLoS ONE, 10(3), e0123690.
Publication 2015
Acinetobacter Blood Carbapenem-Resistant Enterobacteriaceae carbapenemase Carbapenems Domestic Sheep Enterobacteriaceae Genes Meropenem Pseudomonas Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
5
National Healthcare Safety Network (NHSN) Pathogens Report
The CLABSIs,7 CAUTIs,8 select VAEs,9 and SSIs10 that occurred between 2015–2017 and had been reported to the NHSN’s Patient Safety Component as of July 1, 2018, were included in this report. These HAIs were reported by acute-care hospitals, critical access hospitals, LTACHs, and IRFs from all US states and territories. Unless otherwise noted, CLABSI data included events classified as mucosal barrier injury laboratory-confirmed bloodstream infection (MBI-LCBI). VAE data were limited to events classified as possible ventilator-associated pneumonia (PVAP) because this is the only subtype of VAE for which a pathogen can be reported. Asymptomatic bacteremic urinary tract infections, CLABSIs reported from IRFs, and outpatient SSIs were excluded.
The NHSN protocols provide guidance for attributing device-associated (DA) HAIs (ie, CLABSIs, CAUTIs, and PVAPs) to a CDC-defined location type, and SSIs to a CDC operative procedure code. Due to known differences in pathogens and resistance patterns between adult and pediatric populations,11 ,12 (link) this report was limited to DA HAIs attributed to adult location types, and to SSIs that occurred in patients ≥18 years old at the time of surgery. Comparable data from pediatric locations and patients are described in a companion report.13 (link)Unless otherwise noted, DA HAIs were stratified into 5 mutually exclusive location categories: hospital wards (inclusive of step-down, mixed acuity, and specialty care areas), hospital intensive care units (ICUs), hospital oncology units (ie, oncology ICUs and wards), LTACHs (ie, LTACH ICUs and wards), and IRFs (ie, freestanding IRFs and CMS-certified IRF units located within a hospital). SSI data were stratified into mutually exclusive surgical categories based on the operative procedure code. Pathogen distributions were also analyzed separately for each operative procedure code and are available in the online supplement.14 Up to 3 pathogens and their antimicrobial susceptibility testing (AST) results can be reported to the NHSN for each HAI. The AST results for the drugs included in this analysis were reported using the interpretive categories of “susceptible” (S), “intermediate” (I), “resistant” (R), or “not tested.” Instead of “intermediate,” cefepime had the category interpretation of “intermediate/susceptible-dose dependent” (I/S-DD), which was treated as I for this analysis. Laboratories are expected to follow current guidelines from the Clinical and Laboratory Standards Institute (CLSI) for AST.15 Naming conventions for pathogens generally adhered to the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) Preferred Term.16 In some cases, pathogens were grouped by genus or clinically recognized group (eg, viridans group streptococci) (Appendices A2–A4 online). Results for Klebsiella spp were limited to K. pneumoniae and K. oxytoca; K. aerogenes was considered part of Enterobacter spp due to the timing of the NHSN’s adoption of its name change.17 (link)Staphylococcus aureus was defined as methicillin-resistant (MRSA) if the isolate was reported as R to oxacillin, cefoxitin, or methicillin. Enterococcus spp isolates were defined as vancomycin-resistant (VRE) if they tested R to vancomycin. VRE data were analyzed for all HAIs except PVAP because Enterococcus spp are excluded from the NHSN’s PVAP surveillance definition under most scenarios. Carbapenem-resistant Enterobacteriaceae (CRE) were defined as Klebsiella spp, Escherichia coli, or Enterobacter spp that tested R to imipenem, meropenem, doripenem, or ertapenem. All other pathogen-antimicrobial combinations (phenotypes) were described using a metric for nonsusceptibility, which included pathogens that tested I or R to the applicable drugs. To be defined as nonsusceptible to extended-spectrum cephalosporins (ESCs), pathogens must have tested I or R to either ceftazidime or cefepime (Pseudomonas aeruginosa) or to ceftazidime, cefepime, ceftriaxone, or cefotaxime (Klebsiella spp and E. coli). For Enterobacter spp, evaluation of nonsusceptibility to ESCs was limited to cefepime due to Enterobacter’s inducible resistance to other ESCs. Fluoroquinolone nonsusceptibility was defined as a result of I or R to either ciprofloxacin or levofloxacin (P. aeruginosa) or to ciprofloxacin, levofloxacin, or moxifloxacin (E. coli). Carbapenem nonsusceptibility in P. aeruginosa and Acinetobacter spp was defined as a result of I or R to imipenem, meropenem, or doripenem. Nonsusceptibility to aminoglycosides was defined as a result of I or R to gentamicin, amikacin, or tobramycin. Finally, multi-drug-resistance (MDR) was approximated by adapting previously established definitions18 (link) that require nonsusceptibility to at least 1 agent within 3 different drug classes. For Enterobacteriaceae and P. aeruginosa, 5 classes were considered in the criteria: ESCs (or cefepime for Enterobacter spp), fluoroquinolones, aminoglycosides, carbapenems, and piperacillin (PIP) or piperacillin/tazobactam (PIPTAZ). A sixth class, ampicillin/sulbactam, was included in the criteria for Acinetobacter spp.
Data were analyzed using SAS version 9.4 software (SAS Institute, Cary, NC). For all HAIs and pathogens, absolute frequencies and distributions were calculated by HAI, location, and surgical category. The 15 most commonly reported pathogens were identified, and their frequencies and ranks within each stratum were calculated. A pooled mean percentage nonsusceptible (%NS) was calculated for each phenotype as the sum of nonsusceptible (or resistant) pathogens, divided by the sum of pathogens tested for susceptibility, and multiplied by 100. Percentage NS was not calculated for any phenotype for which <20 pathogens were tested. Differences in the %NS across location types or surgical categories were assessed for statistical significance using a mid-P exact test, and P < .05 was considered statistically significant. The percentage of pathogens with reported susceptibility results (referred to as “percentage tested”) is defined elsewhere3 (link) and was calculated for each bacterial phenotype, as well as for select Candida spp. Pathogens and susceptibility data for CLABSIs categorized as MBI-LCBI were analyzed separately and are presented in the online supplement.14 “Selective reporting” occurs when laboratories suppress AST results as part of antimicrobial stewardship efforts. This practice could contribute to a higher number of pathogens reported to the NHSN as “not tested” to certain drugs. To assess the impact of selective reporting on the national %NS, we applied an alternate calculation for CRE and ESC nonsusceptibility. If a pathogen was reported as “not tested” to carbapenems, susceptibility was inferred as S if the pathogen tested susceptible to at least 2 of the following: ampicillin, ampicillin/sulbactam, amoxicillin/clavulanic acid, PIPTAZ, cefazolin, cefoxitin, or cefotetan. If a pathogen was reported as “not tested” to ESCs, susceptibility was inferred as S if the pathogen tested susceptible to at least 2 of the following: ampicillin, aztreonam, or cefazolin. Therefore, the number of tested isolates increases under the alternate calculation. Percentage NS was calculated using both the traditional (ie, strictly as reported) and alternate approaches.
Statistical analyses were not performed to test for temporal changes in the %NS; thus, this report does not convey any conclusions regarding changes in resistance over time. Due to differences in the stratification levels, inclusion criteria, and patient populations, the %NS values in this report should not be compared to those published in previous iterations of this report.
Weiner-Lastinger L.M., Abner S., Edwards J.R., Kallen A.J., Karlsson M., Magill S.S., Pollock D., See I., Soe M.M., Walters M.S, & Dudeck M.A. (2019). Antimicrobial-resistant pathogens associated with adult healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network, 2015–2017. Infection control and hospital epidemiology, 41(1), 1-18.
Publication 2019
Acinetobacter Adult Amikacin Aminoglycosides Amox clav Ampicillin ampicillin-sulbactam Antimicrobial Stewardship Asymptomatic Infections Aztreonam Bacteremia Bacteria Blood Circulation Candida Carbapenem-Resistant Enterobacteriaceae Carbapenems Cefazolin Cefepime Cefotaxime Cefotetan Cefoxitin Ceftazidime Ceftriaxone Cephalosporins Ciprofloxacin Clinical Laboratory Services Conferences Dietary Supplements Doripenem Enterobacter Enterobacteriaceae Enterococcus Ertapenem Escherichia coli Fluoroquinolones Gentamicin Imipenem Injuries Klebsiella Klebsiella oxytoca Klebsiella pneumoniae Laboratory Infection Lanugo Levofloxacin Medical Devices Meropenem Methicillin Methicillin-Resistant Microbicides Moxifloxacin Mucous Membrane Multi-Drug Resistance Neoplasms Operative Surgical Procedures Outpatients Oxacillin pathogenesis Patients Patient Safety Pets Pharmaceutical Preparations Phenotype Piperacillin Piperacillin-Tazobactam Combination Product Pneumonia, Ventilator-Associated polyvinylacetate phthalate polymer Population Group Pseudomonas aeruginosa Sepsis Staphylococcus aureus Infection Streptococcus viridans Substance Abuse Detection Susceptibility, Disease Tobramycin Urinary Tract Vancomycin Vancomycin Resistance Wound Infection

Most recents protocols related to «Enterobacteriaceae»

1
Dictyostelium Strains Suppress Soft Rot Pathogens
Not available on PMC !

Example 1

119 Dicty strains were screened for their ability to feed on Dickeya (Dd) or Pectobacterium (Pcc) at 10° C. This assay was performed by inoculating Dd or Pcc on a low nutrient medium (SM2 agar) that supports both bacterial and Dicty growth. Dicty spores from individual strains were then inoculated on top of the bacterial growth and incubated at 10° C. to mimic potato storage temperatures. Dicty strains that successfully fed on Dd or Pcc created visible clearings in the lawn of bacterial growth and ultimately produced sporangia (fruiting bodies) that rose from the agar surface. An example of the phenotype that was considered successful clearing of bacteria is shown in FIG. 3A. From this initial screen, 36 Dicty strains that were capable of feeding on both Dd and Pcc at 10° C. were identified (FIG. 1B).

Of the 36 strains capable of feeding on both Dd and Pcc, 34 came from the Group 4 Dictyostelids (FIG. 1). This group includes D. discoideum, D. giganteum, D. minutum, D. mucoroides, D. purpureum, and D. sphaerocephalum (72). The results indicate that this group is particularly enriched in Dd and Pcc-feeding strains.

A further experiment was performed to identify Dicty species capable of feeding on biofilms of Dd and Pcc. Microporous polycarbonate membranes (MPMs) are widely reported to support biofilm formation of numerous Enterobacteriaceae species (2, 63, 70, 71). It was determined if Dd and Pcc formed biofilms on MPMs and determined if Dicty strains were capable of feeding on these biofilms. Membranes were placed on top of SM2 agar to provide Dd and Pcc with nutrients for growth. Bacteria were then inoculated on the surface of the MPMs and growth was monitored over the course of 1 week by washing bacteria off the membranes and performing dilution plating for colony counting. Growth of both bacterial strains plateaued around 4 dpi (FIG. 2).

From these results, it was determined that the best time to collect inoculated MPMs for biofilm analysis was at 2 dpi. Scanning electron microscopy (SEM) is commonly used to confirm biofilm formation by detecting extracellular polymeric substance (EPS) that forms the biofilm matrix (2). Samples of Dd and Pcc after 2 days of growth on MPMs in the presence and absence of Dicty are analyzed using SEM.

19 Dicty strains identified as active were tested for their ability to feed on Dd and Pcc growing on MPMs. These experiments were performed by establishing Dd and Pcc growth on MPMs overlaid on SM2 agar at 37° C. for 24 hr. Dicty spores were then applied to the center of bacterial growth in a 5 uL drop containing 1000 spores. Bacteria and Dicty were incubated at 10° C. for 2 weeks before remaining bacteria were washed off and colonies were counted. Representative images of Dicty growing on Dd and Pcc on MPMs are shown in FIG. 3A.

No Dicty strains produced a statistically significant reduction in Dd viability compared to the non-treated control. However, treating Dd lawns with Cohen 36, Cohen 9, WS-15, WS-20, and WS-69 consistently reduced the number of viable bacteria by approximately 100,000-fold compared to the non-treated control (FIG. 3B). Cohen 9 was the only Dicty strain that produced a statistically significant reduction in viability of Pcc compared to the non-treated control (FIG. 3C). Other Dicty strains capable of reducing the number of viable Pcc by at least 100,000-fold were Cohen 35, Cohen 36, WS-647, and WS-69 (FIG. 3C).

It was observed that Dicty strains Cohen 9, Cohen 36, and WS-69 were capable of feeding on both Dd and Pcc when these bacteria were cultured on SM2 agar and MPMs (FIGS. 1 and 3). These strains were also particularly effective feeders as all three reduced the number of viable Dd and Pcc on MPMs at 10° C. by 100,000-fold compared to the non-treated control (FIGS. 3B and 3C).

To determine if these strains could suppress soft rot development on seed potato tubers, tubers were tab-inoculated with Dd or Pcc and treated with spores from each Dicty strain. Seed potatoes were surface-sterilized and punctured using a sterile screw to a depth of 1.5 mm. Overnight cultures of Dd and Pcc were suspended in 10 mM potassium phosphate buffer, diluted to an OD600 of approximately 0.003, and administered as a 5 μL drop into the wound. Next, 5 of a Dicty spore suspension (100,000 spores) was added to the wound. Inoculated seed potatoes were placed in a plastic container with moist paper towels and were misted with water twice a day to maintain a high humidity. After 3 days at room temperature, seed potatoes were sliced in half and the area of macerated tissue was quantified using ImageJ.

All three strains reduced the severity of soft rot caused by Dd and Pcc (FIG. 4). Cohen 36 was the most effective strain on both Dd and Pcc: reducing the area of tissue maceration by 60% and 35%, respectively (FIG. 4B). Treating seed potatoes with WS-69 reduced the area of tissue maceration by 50% and 30% for Dd and Pcc, respectively (FIG. 4B). Finally, Cohen 9 was the least effective, but still able to reduce tissue maceration caused by Dd and Pcc by 25% and 20%, respectively (FIG. 4B).

FIG. 7 shows that three Dicty isolates control Dd and Pcc in seed tubers (at 25° C.). Two sets of data from different weeks were normalized to the Dickeya or Pectobacterium only bacterial control. The average area of macerated potato tissue measured in mm2 was set as “1” or “100%”. The average of all the other treatments including Dicty were divided by bacteria only control and multiplied by 100 to obtain a percentage. Each set contained 5 tubers per treatment.

Dicty should be capable of sporulating at temperatures as cold as 10° C. on a potato surface if they are applied as a one-time pre-planting or post-harvest treatment. Sporulation was assessed by inoculating small potato discs (5×6 mm) with 10 μL of Dd or Pcc suspensions at an OD600 of 3×10−5 and Dicty spores at a concentration of 1×107 spores/mL. Potato discs were kept in a covered 96-well plate for two weeks at 10° C. followed by visual inspection for son using a dissecting microscope. Representative images of a strain producing many sori (WS-517) and a strain producing few sori (WS-69) are shown in FIG. 5. Of the 11 strains evaluated, only Cohen 9 and WS-20 were unable to sporulate in the presence of both pathogens (Table 1).

TABLE 1
Assessment of Dicty sporulation at 10° C. on potato
in the presence of Dd or Pcc. A (✓) indicates sori
have been observed while a ( [Figure (not displayed)]  ) means they have not.
Dicty strainDdPcc
Cohen 9✓[Figure (not displayed)]
Cohen 36✓✓
WS-69✓✓
WS-517✓✓
WS-588✓✓
WS-606✓✓
WS-15✓✓
WS-20[Figure (not displayed)] ✓
DC-7✓✓
DC-61✓✓
WS-116d✓✓

Example 2

This example describes the use of a high throughput screening assay to identify Dicty strains from Alaska (e.g., BAC10A, BAF6A, BAC3A, NW2, KB4A (ATCC® MYA-4262™) SO8B, SO3A, BAF9B, IC2A (ATCC® MYA-4259™), AK1A1 (ATCC® MYA-4272™) PBF4B (ATCC® MYA-4263), PBF8B, BSB1A, SO5B (ATCC® MYA-4249), PBF3C, PBF6B, NW2B, NW10B (ATCC® MYA-4271™), PBF9A, IC5A (ATCC® MYA-4256TH), ABC8A (ATCC® MYA-4260), NW16B, ABC10B, ABB6B (ATCC® MYA-4261), BA4A (ATCC® MYA-4252), AKK5A, AKK52C, HP4 (ATCC® MYA-4286), HP8 (ATCC® MYA-4284), or NW9A) that feed on Dd and Pcc at 10° C. on potatoes.

Results from 11 Dicty strains screened against Dd at 10° C. are presented in FIG. 6. Data was analyzed for significance using a one-way analysis of variance (ANOVA; alpha =0.05) with Tukey's honest significant difference (HSD) test to compare means between the treatments and the No Dicty control. A reduction in Dd proliferation when potato discs were treated with Dicty strains Cohen 9, Cohen 36, WS-15, Maryland 18a, BAF6A, NW2, and SO3A.

The Alaskan Dicty strains, and those identified in Example 1, are further tested against coinfections of Dd and Pcc. It is useful to identify Dicty strains that can suppress Dd and Pcc coinfections as these two pathogens have been isolated together from diseased potatoes (15). The ability of Dicty strains with different feeding preferences (Dd vs. Pcc) to complement each other when administered as a cotreatment is assayed.

US11864559B2. Therapeutic amoeba and uses thereof (2024-01-09). AmebaGone, LLC [US]. Inventors: Marcin Filutowicz [US], Ryan Kessens [US], Amy Jancewicz [US].
Patent 2024
A-A-1 antibiotic Agar Amoeba Bacteria Biofilms Buffers Coinfection Cold Temperature Combined Modality Therapy Dickeya Dictyosteliida Enterobacteriaceae Extracellular Polymeric Substance Matrix Extracellular Polymeric Substances High-Throughput Screening Assays Human Body Humidity Microscopy neuro-oncological ventral antigen 2, human Nutrients Pathogenicity Pectobacterium Phenotype Plant Tubers polycarbonate potassium phosphate Scanning Electron Microscopy Solanum tuberosum Sporangia Spores Sterility, Reproductive Strains Technique, Dilution Tissue, Membrane Tissues Wounds
2
FISH Analysis of Gut Microbial Composition
FISH was performed using an automated device (Biotrack analyzer; Biotrack B.V.; Leeuwarden, Netherlands). Fluorescent probes for F. prausnitzii (Fprau645), Clostridium group XIVa (Erec482), Roseburia (Rint623), Enterobacteriaceae (EC1535), and total bacteria (EUB338) were used to measure the effect of the riboflavin intervention (Benus et al, 2010 (link); Manichanh et al, 2006 (link)). The probe sequences are available in the Supplementary Data.
Liu L., Sadaghian Sadabad M., Gabarrini G., Lisotto P., von Martels J.Z., Wardill H.R., Dijkstra G., Steinert R.E, & Harmsen H.J. (2023). Riboflavin Supplementation Promotes Butyrate Production in the Absence of Gross Compositional Changes in the Gut Microbiota. Antioxidants & Redox Signaling, 38(4), 282-297.
Publication 2023
Bacteria Clostridium Enterobacteriaceae Fishes Fluorescent Probes Medical Devices Riboflavin
3
Quantitative Analysis of Dairy Microbiome
The quantitative PCR primers for Enterobacteriaceae, Streptococcus, Mycoplasma, Lactobacillus, and Bifidobacterium were designed according to the 16S rRNA representative sequences annotated as these genera. The DNA of cow milk bacteria in the antibiotic treatment group and the geraniol treatment group was used as a template for quantitative PCR.The primers and thermocycling parameters are presented in Table S2 and Table S3. Taking the bacteria in the dairy cows’ milk obtained on day 0 as the baseline, the relative quantification of Enterobacteriaceae, Streptococcus, Mycoplasma, Lactobacillus, and Bifidobacterium was calculated on the 3rd, 5th, and 14th days. The 16S rRNA gene was used for bacterial normalization.
Guo W., Qiu M., Pu Z., Long N., Yang M., Ren K., Ning R., Zhang S., Peng F., Sun F, & Dai M. (2023). Geraniol-a potential alternative to antibiotics for bovine mastitis treatment without disturbing the host microbial community or causing drug residues and resistance. Frontiers in Cellular and Infection Microbiology, 13, 1126409.
Publication 2023
Antibiotics Bacteria Bifidobacterium DNA, Bacterial Enterobacteriaceae Genes geraniol Lactobacillus Milk, Cow's Mycoplasma Oligonucleotide Primers Ribosomal RNA Genes RNA, Ribosomal, 16S Streptococcus
4
Biotransformed Composite Flour Analysis
For each sample, 1 g of the biotransformed composite flour mixture was mixed with 9 ml of sterile 0.85% (w/v) NaCl solution, and 1 ml of the suspension mixture was serially diluted with a 10-fold dilution factor. The diluted sample was evaluated for viable cell count using MRS and Eosin Methylene Blue (EMB) agar (Merck, Darmstadt, Germany) to determine the LAB and Enterobacteriaceae growth, respectively. The bacterial growth was expressed as log10 colony forming unit (CFU)/g (16 (link)). All analyses were performed in triplicates.
Koyum K.A., Foo H.L., Ramli N, & Loh T.C. (2023). Biotransformation of gluten-free composite flour mediated by probiotics via solid-state fermentation process conducted under different moisture contents. Frontiers in Nutrition, 10, 910537.
Publication 2023
Agar Bacteria Enterobacteriaceae Eosin factor A Factor X Flour Methylene Blue Sodium Chloride Sterility, Reproductive Technique, Dilution
5
Comprehensive Bacterial Genome Assemblies

De novo short-read assemblies were done with SPAdes (v3.13.0) at default parameters, while de novo hybrid assemblies were done with Unicycler (version v0.4.8) at default parameters. To check for misassemblies, we used read mappings for specific regions of interest such as the chromosomal integrations of blaCTX-M. Reconstructed plasmids were retrieved from the hybrid assemblies. The reconstructed plasmids were identified based on if it was a circular contig and comparisons to databases such as NCBI nt, ResFinder (version 4.1) and PlasmidFinder (version 2.1). ResFinder (version 4.1) was used to determine genes responsible for the genotypic AMR resistance. PlasmidFinder (version 2.1) was used for the detection of plasmid replicons. ISfinder [56 (link)] was used to detect transposase genes. These three databases were queried using the web-tools which are based on blast, applied to the assemblies. Mlplasmid (v2.1.0) [57 (link)], Plasflow (version 1.1) [58 (link)] and MOB-suite (version 3.0.3) [59 (link)], and blast with the NCBI database were used to predict the origin (chromosome or plasmid) of short-read contigs. For Mlplasmid the option E. coli was used on the Shigella isolates due to the high similarity of these species, while with Plasflow the option Enterobacteriaceae was used for all isolates. For local alignments blast (v2.11.0) [60 (link)] was used, while for global alignments MauveProgressive (v 2.4.0) [61 (link)] was used. Genomes were annotated with Prokka (v1.14) [62 (link)], and these annotations were also used to determine the ORFs of genes. The visualization of these annotations was done with BRIG (v0.95) [63 (link)]. The sequence type (ST) was determined by multi-locus sequence typing MLST using blast on assemblies with the Warwick and classic scheme from Enterobase [64 (link)] for Shigella and Salmonella. The genotype of Shigella was determined with Mykrobe [65 (link)] and the output was then parsed with the sonneityping script (https://github.com/katholt/sonneityping).
Berbers B., Vanneste K., Roosens N.H., Marchal K., Ceyssens P.J, & De Keersmaecker S.C. (2023). Using a combination of short- and long-read sequencing to investigate the diversity in plasmid- and chromosomally encoded extended-spectrum beta-lactamases (ESBLs) in clinical Shigella and Salmonella isolates in Belgium. Microbial Genomics, 9(1), mgen000925.
Publication 2023
Chromosomes Enterobacteriaceae Escherichia coli Genes Genome Genotype Hybrids Open Reading Frames Plasmids Replicon Salmonella Shigella Transposase

Top products related to «Enterobacteriaceae»

1
Vitek 2 system by bioMérieux
Sourced in France, United States, Germany, Italy, Macao, United Kingdom, Sweden, Belgium, India, Japan, Brazil
The Vitek 2 system is an automated microbiology platform designed for the rapid identification and antimicrobial susceptibility testing of microorganisms. The system utilizes miniaturized biochemical testing to provide accurate results for a wide range of bacterial and yeast species.
2
Vitek 2 by bioMérieux
Sourced in France, United States, Germany, Italy, United Kingdom, Canada, Poland, Macao
The Vitek 2 is a compact automated microbiology system designed for the identification and antimicrobial susceptibility testing of clinically significant bacteria and yeasts. The system utilizes advanced colorimetric technology to enable rapid and accurate results for clinical decision-making.
3
Etest by bioMérieux
Sourced in France, Sweden, United States, Germany, United Kingdom, Denmark, Italy, Australia, Spain, Switzerland, Japan
Etest is a quantitative antimicrobial susceptibility testing (AST) method developed by bioMérieux. It provides minimum inhibitory concentration (MIC) values for specific antimicrobial agents. Etest utilizes a predefined antimicrobial gradient on a plastic strip to determine the MIC of a tested microorganism.
4
Api 20e by bioMérieux
Sourced in France, United States, United Kingdom, Germany, Japan, Macao, Denmark, Italy
The API 20E is a standardized identification system for Enterobacteriaceae and other non-fastidious Gram-negative rods. It consists of 20 miniaturized biochemical tests, which allow the identification of the most frequently encountered members of the Enterobacteriaceae family as well as certain other Gram-negative bacteria.
5
Maldi tof ms by Bruker
Sourced in Germany, United States, France, United Kingdom, Japan, Italy, Switzerland, Canada, Poland
MALDI-TOF MS is a type of mass spectrometry instrument that uses Matrix-Assisted Laser Desorption/Ionization (MALDI) as the ionization technique and Time-of-Flight (TOF) as the mass analyzer. It is designed to analyze and identify a wide range of compounds, including proteins, peptides, lipids, and small molecules.
6
Macconkey agar by Thermo Fisher Scientific
Sourced in United Kingdom, United States, Germany, Italy, India, Canada, Poland, France, Australia, Spain, Belgium
MacConkey agar is a selective and differential culture medium used for the isolation and identification of Gram-negative enteric bacteria, particularly members of the Enterobacteriaceae family. It inhibits the growth of Gram-positive bacteria while allowing the growth of Gram-negative bacteria.
7
Violet red bile glucose agar by Thermo Fisher Scientific
Sourced in United Kingdom
Violet Red Bile Glucose Agar is a culture medium used for the selective isolation and enumeration of Enterobacteriaceae in food and water samples. It contains bile salts, crystal violet, and glucose as the principal components.
8
Plate count agar by Thermo Fisher Scientific
Sourced in United Kingdom, Italy, Germany, United States
Plate Count Agar is a culture medium used for the enumeration of microorganisms in food, water, and other samples. It provides a standardized growth environment to support the growth of a wide range of bacteria, yeast, and mold species. The agar supports the formation of discrete colonies, allowing for accurate counting and identification of microbial populations.
9
Api 20e system by bioMérieux
Sourced in France, United States, Italy, United Kingdom
The API 20E system is a standardized identification system for Enterobacteriaceae and other non-fastidious Gram-negative rods. It consists of a plastic strip with 20 microtubes containing dehydrated biochemical test substrates. The organism is inoculated into the strip, and the reactions that occur during the incubation period are used to identify the bacterial species.
10
16s rrna gene primers by TIB Molbiol
Sourced in Germany
16S rRNA gene primers are oligonucleotide sequences designed to target and amplify specific regions of the 16S ribosomal RNA gene, which is commonly used for the identification and classification of bacteria and archaea. These primers are essential tools in molecular biology, microbiology, and environmental studies.

More about "Enterobacteriaceae"

Enterobacteriaceae is a large family of Gram-negative bacteria that includes many medically significant species, such as Escherichia, Salmonella, Shigella, and Klebsiella.
These pathogens are capable of causing a wide range of infections, from gastrointestinal issues to urinary tract infections and sepsis.
Researchers studying Enterobacteriaceae can leverage innovative platforms like PubCompare.ai to optimize their work through AI-driven protocol comparisons.
PubCompare.ai helps researchers locate the best protocols from literature, preprints, and patents, enhancing reproducibility and streamlining the research process.
This data-driven approach supports decision-making and can be particularly useful for researchers working with common Enterobacteriaceae identification methods like the Vitek 2 system, Etest, API 20E, and MALDI-TOF MS.
These techniques, combined with growth media like MacConkey agar, Violet Red Bile Glucose Agar, and Plate Count Agar, can aid in the detection and characterization of Enterobacteriaceae species.
The 16S rRNA gene primers are another valuable tool for researchers studying the phylogenetic relationships and taxonomic classification of Enterobacteriaceae.
By incorporating these insights and utilizing platforms like PubCompare.ai, researchers can drive their Enterobacteriaceae research forward in a more efficient and data-driven manner, ultimately leading to improved understanding and better patient outcomes.