Systematic real-time profiling of Salmonella type III effector translocation provides quantitative resolution of the T3SS-1/T3SS-2 secretion dichotomy

This study establishes a systematic real-time profiling framework using HiBiT-tagging and split NanoLuc detection to map the temporal translocation kinetics of all 39 Salmonella type III effectors during a 24-hour infection, revealing distinct secretion patterns and a quantitatively resolved functional overlap between T3SS-1 and T3SS-2.

The Gist

The Big Picture: A Bacterial Heist

Imagine Salmonella (the bacteria that causes food poisoning) as a highly organized criminal gang trying to break into a bank (your body's cells). To succeed, they can't just smash the door down; they need to sneak in, disable the security system, and set up a safe room to hide and multiply.

To do this, the bacteria use two different "injection machines" (called Type III Secretion Systems, or T3SS-1 and T3SS-2) to shoot a toolkit of 40 special tools (called effectors) into the cell. These tools hack the cell's software, turning off alarms and opening the vault.

For a long time, scientists thought the bacteria used one machine to break in (T3SS-1) and then immediately switched to a completely different machine to stay inside (T3SS-2). They thought it was a strict "switch": First you use Tool A, then you throw it away and use Tool B.

This paper changes that story. The researchers found that the bacteria are actually much more flexible. They use both machines at the same time, and many of the tools can be fired from either machine depending on the situation.

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The New Spy Tech: The "Glow-in-the-Dark" Tag

The problem with studying this before was that it was like trying to watch a heist in the dark. Scientists could only take snapshots at the end of the night and guess what happened.

In this study, the researchers invented a super-smart way to watch the heist in real-time.

• The Trick: They attached a tiny, invisible "glow-in-the-dark" tag (called HiBiT) to every single bacterial tool.
• The Receiver: They gave the bank cells (human cells) a special "receiver" (called LgBiT) that glows bright blue whenever it catches a tagged tool.
• The Result: As soon as a bacterium shoots a tool into the cell, the cell lights up. By measuring the brightness over 24 hours, they could see exactly when each tool was delivered and how many were sent.

What They Discovered

1. The "Second Wave" Surprise

Scientists used to think the bacteria stopped using their first injection machine (T3SS-1) once they were inside.

• The Discovery: The bacteria actually have a "second wave." After breaking in, some bacteria escape the initial holding cell and start multiplying wildly in the open cytoplasm of the cell. These "rogue" bacteria turn the first injection machine back on!
• The Analogy: It's like a burglar breaking into a house, getting caught in the hallway, but then realizing the back door is open. They break out into the living room and start shooting tools from their first gun again, even though they are already deep inside the house.

2. The "Dual-Use" Tools

The biggest shock was that the tools aren't locked to specific machines.

• The Discovery: About 40% of the tools can be fired from either the first machine or the second machine.
• The Analogy: Imagine a SWAT team. You thought they had "Riot Guns" for the front door and "Sniper Rifles" for the back window. But this study shows that many of their agents are carrying Swiss Army Knives. They can use the same tool to break down the front door and to pick the lock on the back window, depending on what the situation needs.

3. The Timing is Everything

The bacteria don't just fire tools randomly; they have a strict schedule.

• Early Phase (0–9 hours): They fire the "break-in" tools (like SopB and SptP) to force the door open.
• Middle Phase (9–16 hours): They fire the "dual-use" tools. These are the versatile agents that help the bacteria adapt as they move deeper into the cell.
• Late Phase (16–24 hours): They fire the "maintenance" tools (like SseF and SseG) to build a safe, fortified bunker (the vacuole) where they can hide and multiply safely for the long haul.

4. The "Heavy Hitters"

Not all tools are sent in equal numbers.

• The Discovery: A few specific tools make up the vast majority of the "payload."
• The Analogy: If the bacteria sent 100 tools into the cell, about 70 of them would be just three or four specific types. The rest are sent in small numbers. It's like a construction crew: you need thousands of nails (the common tools) to hold the house together, but only a few specialized hammers or drills (the rare tools) to do the specific heavy lifting.

Why This Matters

This study is like upgrading from a black-and-white photo album to a 4K live-stream of a heist.

1. It breaks the old rules: We no longer have to think of the bacteria's infection strategy as a simple "Step 1, Step 2" process. It's a fluid, overlapping dance.
2. It explains resilience: Because the bacteria can use the same tools with different machines, they are harder to stop. If you block one machine, they might just switch to the other one to fire the same tool.
3. New targets for medicine: By knowing exactly when and how these tools are delivered, scientists can design drugs to jam the injection machines at the exact moment they are most vulnerable, rather than just trying to kill the bacteria generally.

In a Nutshell

Salmonella is a master of disguise and adaptability. It doesn't just switch machines; it blends them. It uses a mix of early, middle, and late tools, often firing the same tool from different machines at different times to ensure it survives and thrives inside your cells. This new "live-stream" technology allows us to finally see the full choreography of this microscopic dance.

Technical Summary

1. Problem Statement

Salmonella enterica serovar Typhimurium utilizes two Type III Secretion Systems (T3SS-1 and T3SS-2) to inject approximately 40 effector proteins (T3Es) into host cells. Historically, these systems were viewed as temporally segregated: T3SS-1 drives epithelial invasion (early stage), while T3SS-2 facilitates intracellular survival and replication within the Salmonella-containing vacuole (SCV) (late stage).

• Knowledge Gap: The temporal dynamics of effector translocation during prolonged infection (beyond the initial invasion phase) remain poorly defined.
• Limitations of Previous Methods: Existing techniques (FRET, enzymatic reporters, fluorescent labeling) suffer from low throughput, limited sensitivity, inability to perform long-term quantitative measurements, or perturbation of host physiology. There is a lack of a scalable, real-time framework to quantify the secretion and translocation of the entire effector repertoire simultaneously over extended infection periods.

2. Methodology

The authors developed a systematic, high-throughput, real-time profiling framework combining endogenous protein tagging with split-luciferase detection.

• Strain Construction:
  • Generated a comprehensive library of S. Typhimurium SL1344 strains where all 39 currently annotated T3Es were endogenously C-terminally tagged with HiBiT (an 11-amino acid peptide) using $\lambda$ Red recombineering. This preserved native regulation and avoided plasmid-based artifacts.
  • Created these strains in three genetic backgrounds: Wild-Type (WT), T3SS-1 deficient ($\Delta invA$), and T3SS-2 deficient ($\Delta ssaV$).
• Detection System (Split NanoLuc):
  • Used HeLa cells stably expressing the large fragment of NanoLuc (LgBiT).
  • Upon translocation of the HiBiT-tagged effector into the host cytosol, it binds LgBiT to reconstitute functional NanoLuc luciferase.
  • Substrates:
    • Vivazine: A pro-substrate allowing continuous, long-term luminescence detection (up to 24+ hours) with a half-life of ~24 hours.
    • Furimazine: Used for high-sensitivity, short-term endpoint validation.
• Experimental Design:
  • Real-time Monitoring: Infections were monitored from 2 to 26 hours post-infection (hpi) using a multimodal plate reader (Spark Cyto 400).
  • Multi-parametric Readouts: Simultaneously measured:
    • Luminescence (RLU): Quantifies effector translocation.
    • Fluorescence (eGFP): Quantifies bacterial load (using a constitutively GFP-expressing strain).
    • Bright-field Imaging: Monitors host cell confluence, size, and lysis.
  • Endpoint Validation: Used HiBiT blotting on Triton X-100 soluble (translocated) and insoluble (bacterial) fractions to verify real-time data.
• Data Analysis:
  • Calculated Area Under the Curve (AUC) for luminescence signals.
  • Classified effectors based on statistical differences in AUC between WT, $\Delta invA$, and $\Delta ssaV$ backgrounds during mid-stage (2–10 hpi) and late-stage (10–24 hpi) infection.

3. Key Contributions

1. First System-Wide Real-Time Map: Provided the first quantitative, real-time translocation kinetics for all 39 annotated T3Es over a full 24-hour infection cycle.
2. Resolution of the "Secretion Dichotomy": Challenged the binary view of T3SS-1 vs. T3SS-2. Demonstrated extensive functional overlap, revealing that nearly half of the translocated effectors utilize both systems.
3. Discovery of a "Second Wave" of T3SS-1: Identified a resurgence of T3SS-1 activity during the mid-to-late infection phase (associated with cytosolic hyper-replication), delivering effectors previously thought to be exclusively early-stage.
4. Quantitative Hierarchy: Established a temporal hierarchy of effector delivery, showing that SPI-1 effectors peak early (9 hpi), dual-system effectors peak intermediately (16 hpi), and SPI-2 effectors peak late (~22.5 hpi).
5. Scalable Platform: Validated a strategy using endogenous HiBiT-tagging and split NanoLuc that is adaptable to other host-pathogen systems and serovars.

4. Key Results

• Expression and Secretion Validation:
  • Successfully validated expression and secretion competence for all 39 HiBiT-tagged effectors under SPI-1 (LB) and SPI-2 (LPM) inducing conditions.
  • Confirmed that C-terminal HiBiT tagging generally preserves native regulation, secretion, and translocation, with minor exceptions (e.g., SipB/SipC tagging slightly impaired translocon function; SifA tagging disrupted prenylation).
• Infection Dynamics:
  • Observed a biphasic bacterial replication pattern: an initial cytosolic hyper-replication phase (5–9 hpi) followed by a plateau and a second phase of vacuolar replication.
  • Cytosolic bacteria (hyper-replicating) re-express T3SS-1, driving a "second wave" of effector delivery.
• Effector Classification (32 detectable effectors):
  • SPI-1 Dependent (10 effectors): e.g., SopB, SptP, SipA. Peak translocation at ~9 hpi.
  • SPI-2 Dependent (7 effectors): e.g., SteD, SseF, SseG. Strictly late-stage (peak ~22.5 hpi).
  • Dual SPI-1/SPI-2 Dependent (15 effectors): ~38% of the repertoire. Includes known dual substrates (SteA, PipB2) and newly identified ones (SifB, SopD2, SseJ, SseL, SseM, SteC). These show significant T3SS-1 delivery during the mid-stage "second wave."
• Quantitative Contribution:
  • Cumulative Output: Dual-system substrates contributed 66.6% of the total translocation signal in WT. SPI-1 restricted effectors contributed 32.8%, while strictly SPI-2 restricted effectors contributed <1%.
  • Top Effectors: SopE (40%), SptP (19%), and SseJ (11%) accounted for ~70% of total cumulative translocation.
• Temporal Stratification:
  • Effectors are not delivered in a simple switch but in a coordinated continuum. Dual-system effectors often peak earlier in $\Delta ssaV$ mutants, suggesting preferential deployment during early intracellular SPI-1 activity.

5. Significance

• Paradigm Shift: The study refutes the strict temporal segregation of T3SS-1 and T3SS-2. Instead, it proposes a model of dynamic, overlapping deployment where both systems function concurrently to support distinct intracellular niches (cytosolic vs. vacuolar).
• Functional Redundancy: The discovery that many "SPI-2" effectors are delivered early via T3SS-1 suggests functional redundancy and the ability of Salmonella to modulate host pathways (e.g., inflammation, trafficking) immediately upon invasion and throughout replication.
• Methodological Advance: The HiBiT/NanoLuc platform offers a robust, non-invasive, and highly sensitive tool for dissecting secretion dynamics, overcoming the limitations of traditional endpoint assays.
• Therapeutic Implications: By mapping the precise timing of effector delivery, the study identifies specific windows (e.g., the mid-phase cytosolic burst) that may be vulnerable to intervention, potentially disrupting the bacterial lifecycle before it establishes a stable niche.

In conclusion, this work provides a high-resolution, quantitative map of Salmonella effector deployment, revealing a complex, flexible, and temporally tuned virulence strategy that relies heavily on the coordinated activity of both secretion systems.