Salmonellosis Cell Models for Research

Disease Burden and Research Significance

Epidemiology and Clinical Impact

Salmonellosis is a major global public health burden. The World Health Organization (WHO) estimates 550 million annual cases of diarrheal disease caused by Salmonella, with 230,000 deaths (WHO, 2015). In the United States, the Centers for Disease Control and Prevention (CDC) reports approximately 1.35 million infections, 26,500 hospitalizations, and 420 deaths annually. Risk factors include consumption of contaminated food (poultry, eggs, meat), contact with reptiles, and poor sanitation. Invasive non-typhoidal Salmonella (iNTS) is a leading cause of bloodstream infections in sub-Saharan Africa, with case fatality rates of 20-25% (WHO, 2018). Typhoid fever, caused by Salmonella Typhi, affects 9 million people annually with 110,000 deaths (WHO, 2019).

Value as a Research Model

Salmonella serves as an excellent model for studying host-pathogen interactions, intracellular survival, and immune evasion. Its genetic tractability, well-annotated genome, and ability to infect diverse cell types make it ideal for mechanistic studies. Key research areas include:

  • • Type III secretion systems (T3SS) and effector protein function.
  • • Salmonella-containing vacuole (SCV) biogenesis and intracellular replication.
  • • Innate immune signaling (NF-kB, inflammasome) and autophagy.
  • • Antibiotic resistance mechanisms and persistence.

Public datasets such as NCBI Gene, UniProt, and GEO provide extensive genomic and transcriptomic resources. Open questions include the role of persister cells in relapse, host-specificity determinants, and the impact of microbiome interactions.

Core Molecular Pathogenesis

Major Carcinogenic Pathways

Salmonella pathogenesis involves multiple pathways that manipulate host cell processes:

1. Type III Secretion System (T3SS-1) mediated invasion:

  • • Injectisome delivers effectors (SipA, SipC, SopB, SopE) into host cells.
  • • Induces actin cytoskeleton rearrangements and membrane ruffling.
  • • Triggers internalization into epithelial cells.

2. Type III Secretion System (T3SS-2) mediated intracellular survival:

  • • Effectors (SifA, SseF, SseG) maintain the Salmonella-containing vacuole (SCV).
  • • Prevents lysosomal fusion and promotes replication.

3. SPI-1 and SPI-2 encoded effectors modulate host immune responses:

  • • SopB activates Akt and promotes SCV maturation.
  • • SptP inhibits MAPK signaling.
  • • AvrA inhibits NF-kB and apoptosis.

4. Metabolic reprogramming:

  • • Salmonella induces glycolysis and glutaminolysis in host cells.
  • • Exploits host nutrients for replication.
High-Frequency Genetic Alterations

Salmonella pathogenicity islands (SPIs) and effector genes are frequently altered or acquired. Key genetic features:

Gene/RegionFrequency (%)Mutation TypeFunctional Effect
SPI-1 (invasion)>95ConservedRequired for epithelial invasion
SPI-2 (survival)>95ConservedRequired for intracellular replication
fimH (fimbriae)VariablePhase variationAdhesion and biofilm formation
gyrA (quinolone resistance)10-30Point mutations (S83F, D87N)Fluoroquinolone resistance
blaCTX-M (ESBL)5-20Horizontal transferBeta-lactam resistance
rpoS (stress response)VariableFrameshift/nonsensePersister cell formation
fliC (flagellin)VariablePhase variationImmune evasion

Data from NCBI Gene, UniProt, and published genomic surveys (e.g., NARMS, WHO GLASS).

Deregulated Signaling Networks

Salmonella effectors target multiple host signaling networks:

  • • NF-kB pathway:
  • • AvrA acetylates and inhibits IkB degradation.
  • • SseL deubiquitinates IkB.
  • • Net effect: reduced pro-inflammatory cytokine production.
  • • MAPK pathway:
  • • SptP tyrosine phosphatase inactivates ERK, JNK, p38.
  • • SopB activates PI3K/Akt.
  • • Promotes cell survival and SCV maturation.
  • • PI3K/Akt/mTOR pathway:
  • • SopB activates Akt via PI3K.
  • • Promotes nutrient uptake and SCV integrity.
  • • Inhibits apoptosis.
  • • Autophagy:
  • • SipA and SopB inhibit autophagosome formation.
  • • SseL and AvrA modulate LC3 lipidation.
  • • Facilitates intracellular survival.
  • • Inflammasome:
  • • Flagellin activates NLRC4 and NAIP.
  • • SPI-1 effectors modulate caspase-1 activation.
  • • Balances inflammation and immune evasion.

Experimental Model Systems

Cell Lines and Organoids

Common cell lines used in Salmonella research:

Cell LineOriginKey Mutations/Features
HeLaHuman cervical carcinomaHPV E6/E7, p53/Rb inactivated
Caco-2Human colorectal adenocarcinomaAPC mutant, p53 mutant
HT-29Human colorectal adenocarcinomaAPC mutant, p53 mutant, BRAF V600E
J774A.1Mouse macrophageTLR4+, phagocytic
RAW 264.7Mouse macrophageTLR4+, phagocytic
THP-1Human monocytePMA-differentiated macrophages
INT-407Human embryonic intestineNon-tumorigenic
OrganoidsHuman/mouse intestinalPrimary, patient-derived

Organoids offer advantages: 3D architecture, mucus layer, polarized epithelium, and patient-specific genetics. They enable studies of host-microbe interactions in a physiologically relevant context.

Animal Models (PDX, GEMM, Induced)

Animal models for Salmonellosis:

  • • Mouse models:
  • • C57BL/6 and BALB/c mice with S. Typhimurium (systemic infection).
  • • Streptomycin-pretreated mice for colitis model.
  • • Nramp1 (Slc11a1) congenic mice for resistance studies.
  • • Humanized mice:
  • • Engrafted with human immune cells or intestinal organoids.
  • • Allow study of human-specific pathogens (S. Typhi).
  • • Non-human primates:
  • • Cynomolgus macaques for typhoid fever modeling.
  • • Zebrafish:
  • • Transparent embryos for live imaging of bacterial dissemination.
  • • Galleria mellonella (wax moth larvae):
  • • Innate immunity model for virulence screening.
  • • PDX (patient-derived xenografts):
  • • Limited for Salmonella due to host specificity, but used for co-infection studies.
Gene-Edited Cell Models

CRISPR-Cas9 gene editing enables the creation of isogenic cell lines with precise genetic modifications to study Salmonella-host interactions. Examples include:

  • • Knockout lines:
  • • NF-kB (RELA) knockout in Caco-2 cells to study inflammation.
  • • NLRP3 knockout in THP-1 cells to dissect inflammasome activation.
  • • ATG5 knockout in HeLa cells to study autophagy evasion.
  • • Knock-in lines:
  • • GFP-LC3 reporter in HeLa cells for autophagy flux.
  • • NF-kB luciferase reporter in A549 cells for NF-kB activation.
  • • Salmonella effector (SopB) knock-in in host cells for localization studies.
  • • Isogenic lines:
  • • p53 wild-type vs. knockout isogenic pairs to study apoptosis.
  • • TLR4 mutant vs. wild-type to study LPS sensing.

Commercially available, sequence-verified gene-edited cell models (e.g., knockouts, knock-ins, reporter lines) accelerate research by providing reproducible, validated tools. These models are generated using CRISPR-Cas9 and quality-controlled by Sanger sequencing and functional assays.

Related Disease

Disease name Disease type

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IFNg Overexpression HEK293 Stable Cell Line EDJ-GQ88 Human 3458 Details Get a Quote
NLRP6 Knockout HCT 116 Cell Line EDJ-KQ21 Human 171389 Details Get a Quote
IL12RB1 Knockout HEK293 Cell Line EDJ-KQ131 Human 3594 Details Get a Quote
IL1B Knockout HEK293 Cell Line EDJ-KQ140 Human 3553 Details Get a Quote
STAT1 Knockout HEK293 Cell Line EDJ-KQ188 Human 6772 Details Get a Quote
IL22 Knockout HEK293 Cell Line EDJ-KQ489 Human 50616 Details Get a Quote
IL6 Knockout HEK293 Cell Line EDJ-KQ498 Human 3569 Details Get a Quote
NLRC4 Knockout HEK293 Cell Line EDJ-KQ505 Human 58484 Details Get a Quote
CXCL8 Knockout HEK293 Cell Line EDJ-KQ559 Human 3576 Details Get a Quote
MYD88 Knockout HEK293 Cell Line EDJ-KQ578 Human 4615 Details Get a Quote
IL1A Knockout HEK293 Cell Line EDJ-KQ676 Human 3552 Details Get a Quote
IL17A Knockout HEK293 Cell Line EDJ-KQ959 Human 3605 Details Get a Quote
NOD1 Knockout HEK293 Cell Line EDJ-KQ1045 Human 10392 Details Get a Quote
AIM2 Knockout HEK293 Cell Line EDJ-KQ1059 Human 9447 Details Get a Quote
ATG16L1 Knockout HEK293 Cell Line EDJ-KQ1068 Human 55054 Details Get a Quote

Applications of Gene-Edited Cells

Functional Genomics

Gene-edited cell lines enable functional validation of host factors identified in genome-wide screens. Examples:

  • • CRISPR knockout of SLC11A1 (NRAMP1) in macrophages confirms its role in restricting Salmonella replication.
  • • Knockout of VAMP8 in HeLa cells impairs SCV maturation.
  • • Knock-in of GFP-tagged Rab5 in HeLa cells allows live imaging of SCV trafficking.
  • • CRISPR interference (CRISPRi) screens identify host dependency factors.

These models help dissect molecular mechanisms and prioritize drug targets.

Drug Screening and Resistance

Isogenic pairs (e.g., wild-type vs. mutant) are used for high-throughput drug screening:

  • • Antibiotic susceptibility testing: knockout of efflux pumps (acrB) in Salmonella or host cells to study resistance.
  • • Host-directed therapies: knockout of host kinases (e.g., AKT1) to identify compounds that block intracellular survival.
  • • Resistance modeling: serial passage of Salmonella in knockout cells to identify resistance mutations.
  • • Combination screens: isogenic lines with defined mutations (e.g., gyrA S83F) to test novel antibiotics.

These approaches accelerate lead optimization and resistance profiling.

Biomarker Discovery

CRISPR synthetic lethality screens in isogenic cell lines identify host genes essential for Salmonella survival:

  • • Genome-wide knockout library in HeLa cells infected with S. Typhimurium identifies host factors (e.g., ARPC2, ARPC3) required for invasion.
  • • CRISPR activation (CRISPRa) screens identify host genes that restrict infection (e.g., IFITM3).
  • • Transcriptomic profiling of knockout lines reveals biomarkers of susceptibility or resistance.
  • • These findings inform diagnostic and prognostic biomarker development.

Public Data Resources

DatabaseURLDescription
WHOhttps://www.who.int/news-room/fact-sheets/detail/salmonella-(non-typhoidal)Global burden, prevention, and control of salmonellosis
NCBI Genehttps://www.ncbi.nlm.nih.gov/geneGene-centric information for Salmonella and host genes
UniProthttps://www.uniprot.orgProtein sequences and functional annotations
GEOhttps://www.ncbi.nlm.nih.gov/geoGene expression datasets from Salmonella infection studies
TCGAhttps://www.cancer.gov/tcgaCancer genomics data (for host-pathogen studies in cancer)
cBioPortalhttps://www.cbioportal.orgVisualization and analysis of cancer genomics data
DepMaphttps://depmap.orgCancer dependency map, including CRISPR screens
ClinVarhttps://www.ncbi.nlm.nih.gov/clinvarClinical variants associated with host susceptibility
COSMIChttps://cancer.sanger.ac.uk/cosmicSomatic mutations in cancer
PATRIChttps://www.patricbrc.orgBacterial genomics and pathogen data
Salmonella Genome Databasehttp://www.sanger.ac.uk/resources/downloads/bacteria/salmonella.htmlGenomic sequences and annotations

Frequently Asked Research Questions

Salmonella enterica serovar Typhimurium (S. Typhimurium) and S. Typhi are the most widely used. S. Typhimurium is used for gastroenteritis models, while S. Typhi is used for typhoid fever studies.
Knockout cell lines allow researchers to delete specific host genes (e.g., autophagy genes, immune signaling components) and assess the impact on bacterial invasion, replication, and immune evasion.
Isogenic lines differ only in the gene of interest, eliminating confounding genetic background effects. This provides a clean platform for target validation and drug screening.
Yes, many commercially available gene-edited cell lines (knockouts, knock-ins, reporter lines) are available from commercial sources. These are sequence-verified and functionally validated, saving time and ensuring reproducibility.
NCBI Gene, UniProt, PATRIC, and the Salmonella Genome Database (Sanger) provide comprehensive genomic and proteomic data. GEO and ArrayExpress host transcriptomic datasets.

Key References and Database URLs

WHO Salmonella (non-typhoidal) fact sheet https://www.who.int/news-room/fact-sheets/detail/salmonella-(non-typhoidal
WHO Typhoid fever fact sheet https://www.who.int/news-room/fact-sheets/detail/typhoid
CDC Salmonella https://www.cdc.gov/salmonella/index.html
NCBI Gene https://www.ncbi.nlm.nih.gov/gene
UniProt https://www.uniprot.org
GEO https://www.ncbi.nlm.nih.gov/geo
TCGA https://www.cancer.gov/tcga
cBioPortal https://www.cbioportal.org
DepMap https://depmap.org
ClinVar https://www.ncbi.nlm.nih.gov/clinvar
COSMIC https://cancer.sanger.ac.uk/cosmic
PATRIC https://www.patricbrc.org
Salmonella Genome Database (Sanger) http://www.sanger.ac.uk/resources/downloads/bacteria/salmonella.html
NARMS (National Antimicrobial Resistance Monitoring System) https://www.fda.gov/animal-veterinary/national-antimicrobial-resistance-monitoring-system
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