scholarly journals Strongyloidiasis complicated by gram-negative bacteremia and liver abscesses

IDCases ◽  
2022 ◽  
pp. e01392
Author(s):  
Eloy E. Ordaya ◽  
Anisha Misra ◽  
Omar M. Abu Saleh
Author(s):  
Jamie L. Wagner ◽  
Kylie C. Markovich ◽  
Katie E. Barber ◽  
Kayla R. Stover ◽  
Lauren R. Biehle

2021 ◽  
Vol 99 (4) ◽  
Author(s):  
Raghavendra G Amachawadi ◽  
Wesley A Tom ◽  
Michael P Hays ◽  
Samodha C Fernando ◽  
Philip R Hardwidge ◽  
...  

Abstract Liver abscesses in feedlot cattle are polymicrobial infections. Culture-based studies have identified Fusobacterium necrophorum as the primary causative agent, but a number of other bacterial species are frequently isolated. The incidence of liver abscesses is highly variable and is affected by a number of factors, including cattle type. Holstein steers raised for beef production have a higher incidence than crossbred feedlot cattle. Tylosin is the commonly used antimicrobial feed additive to reduce the incidence of liver abscesses. The objective of this study was to utilize 16S ribosomal RNA amplicon sequence analyses to analyze the bacterial community composition of purulent material of liver abscesses of crossbred cattle (n = 24) and Holstein steers (n = 24), each fed finishing diet with or without tylosin. DNA was extracted and the V3 and V4 regions of the 16S rRNA gene were amplified, sequenced, and analyzed. The minimum, mean, and maximum sequence reads per sample were 996, 177,070, and 877,770, respectively, across all the liver abscess samples. Sequence analyses identified 5 phyla, 14 families, 98 genera, and 102 amplicon sequence variants (ASV) in the 4 treatment groups. The dominant phyla identified were Fusobacteria (52% of total reads) and Proteobacteria (33%). Of the top 25 genera identified, 17 genera were Gram negative and 8 were Gram positive. The top 3 genera, which accounted for 75% of the total reads, in the order of abundance, were Fusobacterium, Pseudomonas, and Bacteroides. The relative abundance, expressed as percent of total reads, of phyla, family, and genera did not differ (P > 0.05) between the 4 treatment groups. Generic richness and evenness, determined by Shannon–Weiner and Simpson’s diversity indices, respectively, did not differ between the groups. The UniFrac distance matrices data revealed no clustering of the ASV indicating variance between the samples within each treatment group. Co-occurrence network analysis at the genus level indicated a strong association of Fusobacterium with 15 other genera, and not all of them have been previously isolated from liver abscesses. In conclusion, the culture-independent method identified the bacterial composition of liver abscesses as predominantly Gram negative and Fusobacterium as the dominant genus, followed by Pseudomonas. The bacterial community composition did not differ between crossbred and Holstein steers fed finishing diets with or without tylosin.


2021 ◽  
Vol 34 (2) ◽  
Author(s):  
Caitlyn L. Holmes ◽  
Mark T. Anderson ◽  
Harry L. T. Mobley ◽  
Michael A. Bachman

SUMMARY Gram-negative bacteremia is a devastating public health threat, with high mortality in vulnerable populations and significant costs to the global economy. Concerningly, rates of both Gram-negative bacteremia and antimicrobial resistance in the causative species are increasing. Gram-negative bacteremia develops in three phases. First, bacteria invade or colonize initial sites of infection. Second, bacteria overcome host barriers, such as immune responses, and disseminate from initial body sites to the bloodstream. Third, bacteria adapt to survive in the blood and blood-filtering organs. To develop new therapies, it is critical to define species-specific and multispecies fitness factors required for bacteremia in model systems that are relevant to human infection. A small subset of species is responsible for the majority of Gram-negative bacteremia cases, including Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. The few bacteremia fitness factors identified in these prominent Gram-negative species demonstrate shared and unique pathogenic mechanisms at each phase of bacteremia progression. Capsule production, adhesins, and metabolic flexibility are common mediators, whereas only some species utilize toxins. This review provides an overview of Gram-negative bacteremia, compares animal models for bacteremia, and discusses prevalent Gram-negative bacteremia species.


2012 ◽  
Vol 71 (3) ◽  
pp. 261-266 ◽  
Author(s):  
Laura L. Raynor ◽  
Jeffrey J. Saucerman ◽  
Modupeola O. Akinola ◽  
Douglas E. Lake ◽  
J. Randall Moorman ◽  
...  

Author(s):  
Julieta Madrid-Morales ◽  
Aditi Sharma ◽  
Kelly Reveles ◽  
Carolina Velez-Mejia ◽  
Teri Hopkins ◽  
...  

Background: Extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae are increasingly common; however, predicting which patients are likely to be infected with an ESBL pathogen is challenging, leading to increased use of carbapenems. To date, five prediction models have been developed to distinguish between patients infected with ESBL pathogens. The aim of this study was to validate and compare each of these models, to better inform antimicrobial stewardship. Methods: This was a retrospective cohort study of patients with gram-negative bacteremia treated at the South Texas Veterans Health Care System over 3 months from 2018 to 2019. We evaluated isolate, clinical syndrome, and score variables for the five published prediction models/scores: Italian “Tumbarello”, Duke, University of South Carolina (USC), Hopkins Clinical Decision Tree, and Modified Hopkins. Each model was assessed using the receiver-operating-characteristic curve (AUROC) and Pearson correlation. Results: 145 patients were included for analysis, of which 20 (13.8%) were infected with an ESBL E. coli or Klebsiella spp. The most common sources of infection were genitourinary (55.8%) and gastrointestinal/intraabdominal (24.1%) and the most common pathogen was E. coli (75.2%). The prediction model with the strongest discriminatory ability (AUROC) was Tumbarello (0.7556). Correlation between prediction model score and percent ESBL was strongest with Modified Hopkins (R2=0.74). Conclusions: In this veteran population, the Modified Hopkins and Duke prediction models were most accurate in discriminating between gram-negative bacteremia patients when considering both AUROC and correlation. However, given the moderate discriminatory ability, many patients with ESBL Enterobacteriaceae (at least 25%) may still be missed empirically.


Sign in / Sign up

Export Citation Format

Share Document