Salmonellosis Cell Models for Research
Disease Burden and Research Significance
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).
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
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.
Salmonella pathogenicity islands (SPIs) and effector genes are frequently altered or acquired. Key genetic features:
| Gene/Region | Frequency (%) | Mutation Type | Functional Effect |
|---|---|---|---|
| SPI-1 (invasion) | >95 | Conserved | Required for epithelial invasion |
| SPI-2 (survival) | >95 | Conserved | Required for intracellular replication |
| fimH (fimbriae) | Variable | Phase variation | Adhesion and biofilm formation |
| gyrA (quinolone resistance) | 10-30 | Point mutations (S83F, D87N) | Fluoroquinolone resistance |
| blaCTX-M (ESBL) | 5-20 | Horizontal transfer | Beta-lactam resistance |
| rpoS (stress response) | Variable | Frameshift/nonsense | Persister cell formation |
| fliC (flagellin) | Variable | Phase variation | Immune evasion |
Data from NCBI Gene, UniProt, and published genomic surveys (e.g., NARMS, WHO GLASS).
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
Common cell lines used in Salmonella research:
| Cell Line | Origin | Key Mutations/Features |
|---|---|---|
| HeLa | Human cervical carcinoma | HPV E6/E7, p53/Rb inactivated |
| Caco-2 | Human colorectal adenocarcinoma | APC mutant, p53 mutant |
| HT-29 | Human colorectal adenocarcinoma | APC mutant, p53 mutant, BRAF V600E |
| J774A.1 | Mouse macrophage | TLR4+, phagocytic |
| RAW 264.7 | Mouse macrophage | TLR4+, phagocytic |
| THP-1 | Human monocyte | PMA-differentiated macrophages |
| INT-407 | Human embryonic intestine | Non-tumorigenic |
| Organoids | Human/mouse intestinal | Primary, 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 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.
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 |
|---|
Related Services
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| Product name | Cat.No. | Species | Gene ID | |
|---|---|---|---|---|
| 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 |
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Applications of Gene-Edited Cells
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.
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.
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
| Database | URL | Description |
|---|---|---|
| WHO | https://www.who.int/news-room/fact-sheets/detail/salmonella-(non-typhoidal) | Global burden, prevention, and control of salmonellosis |
| NCBI Gene | https://www.ncbi.nlm.nih.gov/gene | Gene-centric information for Salmonella and host genes |
| UniProt | https://www.uniprot.org | Protein sequences and functional annotations |
| GEO | https://www.ncbi.nlm.nih.gov/geo | Gene expression datasets from Salmonella infection studies |
| TCGA | https://www.cancer.gov/tcga | Cancer genomics data (for host-pathogen studies in cancer) |
| cBioPortal | https://www.cbioportal.org | Visualization and analysis of cancer genomics data |
| DepMap | https://depmap.org | Cancer dependency map, including CRISPR screens |
| ClinVar | https://www.ncbi.nlm.nih.gov/clinvar | Clinical variants associated with host susceptibility |
| COSMIC | https://cancer.sanger.ac.uk/cosmic | Somatic mutations in cancer |
| PATRIC | https://www.patricbrc.org | Bacterial genomics and pathogen data |
| Salmonella Genome Database | http://www.sanger.ac.uk/resources/downloads/bacteria/salmonella.html | Genomic sequences and annotations |
Frequently Asked Research Questions
What are the most common Salmonella serovars used in research?
How can CRISPR knockout cell lines help study Salmonella pathogenesis?
What is the advantage of isogenic cell lines over traditional cell lines?
Are there commercially available gene-edited cell models for Salmonella research?
What public databases can I use to find Salmonella genomic data?
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 |