Subtopic Deep Dive

Listeria monocytogenes Comparative Genomics
Research Guide

What is Listeria monocytogenes Comparative Genomics?

Listeria monocytogenes Comparative Genomics compares genomes of L. monocytogenes lineages, hypervirulent clones, and stress adaptation genes across food and clinical isolates to reveal evolution and persistence factors.

Pangenome analyses identify dynamic integration hotspots and mobile genetic elements in the accessory genome (Kuenne et al., 2013). Studies trace evolution across four lineages using multilocus sequence typing (Ragon et al., 2008, 577 citations). High-throughput sequencing links clinical isolates to outbreaks (Gilmour et al., 2010, 325 citations).

Curated Papers

Key Challenges

Why It Matters

Comparative genomics enables precise subtyping for food safety surveillance, as shown in South African listeriosis outbreak traced via whole-genome sequencing (Thomas et al., 2020, 230 citations). It predicts hypervirulent clones' adaptation to dairy products, informing targeted interventions (Maury et al., 2019, 241 citations). Pangenome studies reveal persistence factors in food isolates, improving outbreak investigations (Pightling et al., 2018, 246 citations).

Key Research Challenges

Lineage-specific virulence evolution

Distinguishing adaptive mutations from neutral drift across lineages remains difficult (Ragon et al., 2008). Hypervirulent clones show gut adaptation linked to dairy persistence (Maury et al., 2019). Multilocus typing reveals clonal complexes but lacks resolution for recent divergence.

Pangenome dynamic integration

Accessory genome hotspots drive evolution via mobile elements (Kuenne et al., 2013, 211 citations). Food vs. clinical isolates differ in stress genes, complicating persistence tracking. High genomic plasticity challenges stable subtyping.

Outbreak strain resolution

Whole-genome sequencing identifies sources but requires standardized interpretation (Pightling et al., 2018). Clinical isolates from outbreaks show lineage I biases like listeriolysin S (Cotter et al., 2008, 227 citations). Linking to food chains demands high-resolution metrics.

Essential Papers

A New Perspective on Listeria monocytogenes Evolution

Marie Ragon, Thierry Wirth, Florian Hollandt et al. · 2008 · PLoS Pathogens · 577 citations

Listeria monocytogenes is a model organism for cellular microbiology and host-pathogen interaction studies and an important food-borne pathogen widespread in the environment, thus representing an a...

Host adapted serotypes of <i>Salmonella enterica</i>

Sergio Uzzau, Derek Brown, T. S. Wallis et al. · 2000 · Epidemiology and Infection · 451 citations

Salmonella constitutes a genus of zoonotic bacteria of worldwide economic and health importance. The current view of salmonella taxonomy assigns the members of this genus to two species: S. enteric...

Multistate Outbreaks of Foodborne Illness in the United States Associated With Fresh Produce From 2010 to 2017

Christina K. Carstens, Joelle K. Salazar, Charles Darkoh · 2019 · Frontiers in Microbiology · 405 citations

In the United States, the consumption of fresh fruits and vegetables has increased during recent years as consumers seek to make healthier lifestyle choices. However, the number of outbreaks associ...

Characteristics and distribution of Listeria spp., including Listeria species newly described since 2009

Renato H. Orsi, Martin Wiedmann · 2016 · Applied Microbiology and Biotechnology · 329 citations

High-throughput genome sequencing of two Listeria monocytogenes clinical isolates during a large foodborne outbreak

Matthew W. Gilmour, Morag Graham, Gary Van Domselaar et al. · 2010 · BMC Genomics · 325 citations

Interpreting Whole-Genome Sequence Analyses of Foodborne Bacteria for Regulatory Applications and Outbreak Investigations

Arthur Pightling, James Pettengill, Yan Luo et al. · 2018 · Frontiers in Microbiology · 246 citations

Whole-genome sequence (WGS) analysis has revolutionized the food safety industry by enabling high-resolution typing of foodborne bacteria. Higher resolving power allows investigators to identify or...

Hypervirulent Listeria monocytogenes clones’ adaption to mammalian gut accounts for their association with dairy products

Mylène M. Maury, Hélène Bracq‐Dieye, Lei Huang et al. · 2019 · Nature Communications · 241 citations

Reading Guide

Foundational Papers

Start with Ragon et al. (2008, 577 citations) for lineage evolution framework; Kuenne et al. (2013, 211 citations) for pangenome structure; Gilmour et al. (2010, 325 citations) for outbreak genomics application.

Recent Advances

Maury et al. (2019, 241 citations) on hypervirulent dairy adaptation; Thomas et al. (2020, 230 citations) on real-world outbreak tracing; Pightling et al. (2018, 246 citations) on WGS regulatory use.

Core Methods

Multilocus sequence typing (Ragon et al., 2008); pangenome assembly with dynamic hotspots (Kuenne et al., 2013); SNP-based phylogenomics (Gilmour et al., 2010).

How PapersFlow Helps You Research Listeria monocytogenes Comparative Genomics

Discover & Search

Research Agent uses searchPapers('Listeria monocytogenes pangenome') to find Kuenne et al. (2013), then citationGraph reveals 211 citing papers on accessory genomes, and findSimilarPapers expands to hypervirulent clones like Maury et al. (2019). exaSearch queries 'Listeria lineage evolution food isolates' for Ragon et al. (2008, 577 citations).

Analyze & Verify

Analysis Agent applies readPaperContent on Gilmour et al. (2010) to extract outbreak genome variants, verifyResponse with CoVe checks lineage assignments against Ragon et al. (2008), and runPythonAnalysis computes SNP distances from FASTA files using pandas for phylogenetic verification. GRADE grading scores evidence strength for stress gene claims.

Synthesize & Write

Synthesis Agent detects gaps in lineage II persistence via contradiction flagging between Orsi & Wiedmann (2016) and Maury et al. (2019); Writing Agent uses latexEditText for comparative tables, latexSyncCitations integrates 10 papers, latexCompile generates PDF, and exportMermaid diagrams pangenome core-accessory flows.

Use Cases

"Analyze SNP differences in L. monocytogenes outbreak genomes from Gilmour 2010"

Analysis Agent → readPaperContent(Gilmour 2010) → runPythonAnalysis(pandas SNP distance matrix on FASTA) → matplotlib phylogeny plot exported as PNG.

"Draft review on Listeria pangenome evolution with citations"

Synthesis Agent → gap detection → Writing Agent → latexEditText(intro + methods) → latexSyncCitations(Ragon 2008, Kuenne 2013) → latexCompile → PDF review draft.

"Find code for Listeria comparative phylogenomics"

Research Agent → paperExtractUrls(Kuenne 2013) → paperFindGithubRepo → githubRepoInspect → runPythonAnalysis(Iqtree phylogeny on sample genomes).

Automated Workflows

Deep Research workflow scans 50+ papers via searchPapers('Listeria comparative genomics'), structures report with lineage evolution from Ragon et al. (2008). DeepScan applies 7-step CoVe to verify pangenome claims in Kuenne et al. (2013) with GRADE checkpoints. Theorizer generates hypotheses on hypervirulent adaptation from Maury et al. (2019) + outbreak data.

Try Doxa for Listeria monocytogenes Comparative Genomics Research

Frequently Asked Questions

What is Listeria monocytogenes Comparative Genomics?

It compares genomes across lineages and isolates to identify evolution, virulence, and persistence factors (Ragon et al., 2008).

What methods are used?

Pangenome analysis reveals accessory genome hotspots (Kuenne et al., 2013); whole-genome sequencing enables outbreak subtyping (Gilmour et al., 2010).

What are key papers?

Ragon et al. (2008, 577 citations) on evolution; Kuenne et al. (2013, 211 citations) on pangenome; Maury et al. (2019, 241 citations) on hypervirulent clones.