Subtopic Deep Dive

Elizabethkingia meningoseptica Pathogenesis
Research Guide

What is Elizabethkingia meningoseptica Pathogenesis?

Elizabethkingia meningoseptica pathogenesis encompasses the mechanisms by which this Gram-negative bacterium causes neonatal meningitis, bacteremia in immunocompromised patients, and nosocomial outbreaks through virulence factors like capsular polysaccharides and metallo-β-lactamases.

Research focuses on Elizabethkingia species, including E. meningoseptica and E. anophelis, linked to high-mortality infections via genomic epidemiology and resistance mechanisms. Key studies identify hospital transmission clusters and tigecycline resistance origins. Over 20 papers from 2007-2020 detail outbreaks, with top-cited works exceeding 200 citations.

Curated Papers

Key Challenges

Why It Matters

Elizabethkingia outbreaks in neonatal ICUs and immunocompromised patients drive high mortality rates, as shown in Lau et al. (2016) reporting clinically significant bacteremia and Perrin et al. (2017) analyzing the Wisconsin outbreak strain. Resistance via GOB metallo-β-lactamase (Morán-Barrio et al., 2007) and tet(X) gene (Zhang et al., 2020) complicates treatment in hemodialysis and critical care settings (Ratnamani and Rao, 2013; Moore et al., 2015). Genomic insights from Breurec et al. (2016) enable outbreak tracing, informing infection control in hospitals.

Key Research Challenges

Diagnostic Misidentification

Non-fermenter morphology leads to frequent misidentification of Elizabethkingia as other Flavobacteriaceae. Lin et al. (2019) highlight diagnostic gaps in immunocompromised infections. Whole-genome sequencing resolves species differentiation (Perrin et al., 2017).

Intrinsic Multidrug Resistance

GOB metallo-β-lactamase confers resistance to most β-lactams (Morán-Barrio et al., 2007). tet(X) gene emergence links to tigecycline failure (Zhang et al., 2020). Limited susceptibility data hinders therapy (Choi et al., 2018).

Transmission Source Tracing

Hospital water sources and mother-to-infant routes complicate outbreak control (Moore et al., 2015; Lau et al., 2015). Genomic epidemiology reveals clusters but ancestral reservoirs remain unclear (Breurec et al., 2016).

Essential Papers

Elizabethkingia anophelis bacteremia is associated with clinically significant infections and high mortality

Susanna K. P. Lau, Franklin Wang‐Ngai Chow, Chuen-Hing Foo et al. · 2016 · Scientific Reports · 203 citations

Evolutionary dynamics and genomic features of the Elizabethkingia anophelis 2015 to 2016 Wisconsin outbreak strain

Amandine Perrin, Élise Larsonneur, Ainsley Nicholson et al. · 2017 · Nature Communications · 182 citations

Elizabethkingia Infections in Humans: From Genomics to Clinics

Jiun‐Nong Lin, Chung‐Hsu Lai, Chih-Hui Yang et al. · 2019 · Microorganisms · 152 citations

The genus Elizabethkingia has recently emerged as a cause of life-threatening infections in humans, particularly in immunocompromised patients. Several new species in the genus Elizabethkingia have...

Genomic epidemiology and global diversity of the emerging bacterial pathogen Elizabethkingia anophelis

Sébastien Breurec, Alexis Criscuolo, Laure Diancourt et al. · 2016 · Scientific Reports · 101 citations

Epidemiological and phylogenetic analysis reveals Flavobacteriaceae as potential ancestral source of tigecycline resistance gene tet(X)

Rong Zhang, Ning Dong, Zhangqi Shen et al. · 2020 · Nature Communications · 94 citations

Abstract Emergence of tigecycline-resistance tet (X) gene orthologues rendered tigecycline ineffective as last-resort antibiotic. To understand the potential origin and transmission mechanisms of t...

Evidence for<i>Elizabethkingia anophelis</i>Transmission from Mother to Infant, Hong Kong

Susanna K. P. Lau, Alan Wu, Jade L. L. Teng et al. · 2015 · Emerging infectious diseases · 91 citations

Elizabethkingia anophelis, recently discovered from mosquito gut, is an emerging bacterium associated with neonatal meningitis and nosocomial outbreaks. However, its transmission route remains unkn...

Waterborne<i>Elizabethkingia meningoseptica</i>in Adult Critical Care1

Luke Moore, Daniel S. Owens, Annette Jepson et al. · 2015 · Emerging infectious diseases · 82 citations

Elizabethkingia meningoseptica is an infrequent colonizer of the respiratory tract; its pathogenicity is uncertain. In the context of a 22-month outbreak of E. meningoseptica acquisition affecting ...

Reading Guide

Foundational Papers

Start with Ceyhan and Çelik (2011, 80 citations) for neonatal infection overview and Morán-Barrio et al. (2007, 76 citations) for GOB enzyme structure, establishing resistance and clinical context.

Recent Advances

Study Perrin et al. (2017, 182 citations) for outbreak genomics and Zhang et al. (2020, 94 citations) for tet(X) epidemiology to grasp current transmission and resistance dynamics.

Core Methods

Core techniques include whole-genome sequencing (Breurec et al., 2016), phylogenetic analysis (Perrin et al., 2017), and metallo-β-lactamase characterization (Morán-Barrio et al., 2007).

How PapersFlow Helps You Research Elizabethkingia meningoseptica Pathogenesis

Discover & Search

Research Agent uses searchPapers and exaSearch to find outbreak-specific papers like Perrin et al. (2017) on Wisconsin strain dynamics. citationGraph maps transmission studies from Lau et al. (2016) to Breurec et al. (2016), while findSimilarPapers expands to tet(X) resistance (Zhang et al., 2020).

Analyze & Verify

Analysis Agent applies readPaperContent to extract virulence genes from Lin et al. (2019), verifies resistance claims via verifyResponse (CoVe) against Morán-Barrio et al. (2007), and runs PythonAnalysis for phylogenetic tree plotting from Perrin et al. (2017) genomes using NumPy/pandas. GRADE grading scores evidence strength for outbreak causality.

Synthesize & Write

Synthesis Agent detects gaps in neonatal transmission post-Lau et al. (2015), flags contradictions in resistance profiles. Writing Agent uses latexEditText for pathogenesis reviews, latexSyncCitations for 20+ papers, latexCompile for figures, and exportMermaid for transmission flowcharts.

Use Cases

"Phylogenetic analysis of Elizabethkingia outbreak genomes from Wisconsin"

Research Agent → searchPapers('Elizabethkingia Wisconsin outbreak') → Analysis Agent → runPythonAnalysis (load Perrin 2017 genomes, NumPy dendrogram) → matplotlib plot of clusters.

"Draft LaTeX review on E. meningoseptica resistance mechanisms"

Synthesis Agent → gap detection (Morán-Barrio 2007 + Zhang 2020) → Writing Agent → latexEditText (pathogenesis section) → latexSyncCitations (10 papers) → latexCompile → PDF with resistance diagram.

"Find code for Elizabethkingia genomic epidemiology analysis"

Research Agent → paperExtractUrls (Breurec 2016) → paperFindGithubRepo → githubRepoInspect (phylogeny scripts) → runPythonAnalysis (adapt for tet(X) trees).

Automated Workflows

Deep Research workflow scans 50+ papers via searchPapers on 'Elizabethkingia meningoseptica pathogenesis', chains citationGraph to foundational works (Ceyhan 2011), outputs structured report with GRADE scores. DeepScan applies 7-step CoVe to verify transmission claims from Moore et al. (2015). Theorizer generates hypotheses on waterborne virulence from Lau et al. (2016) + Ratnamani (2013).

Try Doxa for Elizabethkingia meningoseptica Pathogenesis Research

Frequently Asked Questions

What defines Elizabethkingia meningoseptica pathogenesis?

It involves neonatal meningitis, immunocompromised bacteremia, and outbreaks driven by capsular polysaccharides and GOB metallo-β-lactamase (Morán-Barrio et al., 2007; Ceyhan and Çelik, 2011).

What are key methods in this research?

Whole-genome sequencing traces outbreaks (Perrin et al., 2017; Breurec et al., 2016), while susceptibility testing reveals resistance patterns (Choi et al., 2018).

What are pivotal papers?

Lau et al. (2016, 203 citations) on bacteremia mortality; Perrin et al. (2017, 182 citations) on Wisconsin genomics; Lin et al. (2019, 152 citations) from genomics to clinics.

What open problems persist?

Unresolved ancestral reservoirs for tet(X) (Zhang et al., 2020), optimal therapies beyond resistance profiles, and rapid diagnostics for non-fermenters.