TAC-TIC, a high-throughput genetics method to identify triggers or blockers of bacterial toxin-antitoxin systems.

Toxin-antitoxin systems (TAs) are abundant in bacterial chromosomes and can arrest growth under stress, but usually remain inactive. TAs have been increasingly implicated in halting the growth of infected bacteria from bacteriophages or foreign genetic elements1,2 to protect the population (abortive infection, Abi). The vast diversity and abundance of TAs and other Abi systems3 suggest they play an important immunity role, yet what allows them to sense attack remains largely enigmatic. Here, we describe a method called toxin activation-inhibition conjugation (TAC-TIC), which we used to identify gene products that trigger or block the toxicity of phage-defending tripartite retron-TAs4. TAC-TIC employs high-density arrayed mobilizable gene-overexpression libraries, which are transferred into cells carrying the full TA system or only its toxic component, on inducible vectors. The double-plasmid transconjugants are then pinned on inducer-containing agar plates and their colony fitness is quantified to identify gene products that trigger a TA to inhibit growth (TAC), or that block it from acting (TIC). TAC-TIC is optimized for the Singer ROTOR pinning robot, but can also be used with other robots or manual pinners, and allows screening tens of thousands of genes against any TA or Abi (with toxicity) within a week. Finally, we present a dual conjugation donor/cloning strain (Escherichia coli DATC), which accelerates the construction of TAC-TIC gene-donor libraries from phages, enabling the use of TAC-TIC for identifying TA triggers and antidefense mechanisms in phage genomes.

High-throughput anaerobic screening for identifying compounds acting against gut bacteria in monocultures or communities.

The human gut microbiome is a key contributor to health, and its perturbations are linked to many diseases. Small-molecule xenobiotics such as drugs, chemical pollutants and food additives can alter the microbiota composition and are now recognized as one of the main factors underlying microbiome diversity. Mapping the effects of such compounds on the gut microbiome is challenging because of the complexity of the community, anaerobic growth requirements of individual species and the large number of interactions that need to be quantitatively assessed. High-throughput screening setups offer a promising solution for probing the direct inhibitory effects of hundreds of xenobiotics on tens of anaerobic gut bacteria. When automated, such assays enable the cost-effective investigation of a wide range of compound-microbe combinations. We have developed an experimental setup and protocol that enables testing of up to 5,000 compounds on a target gut species under strict anaerobic conditions within 5 d. In addition, with minor modifications to the protocol, drug effects can be tested on microbial communities either assembled from isolates or obtained from stool samples. Experience in working in an anaerobic chamber, especially in performing delicate work with thick chamber gloves, is required for implementing this protocol. We anticipate that this protocol will accelerate the study of interactions between small molecules and the gut microbiome and provide a deeper understanding of this microbial ecosystem, which is intimately intertwined with human health.

Randomly barcoded transposon mutant libraries for gut commensals I: Strategies for efficient library construction.

Randomly barcoded transposon mutant libraries are powerful tools for studying gene function and organization, assessing gene essentiality and pathways, discovering potential therapeutic targets, and understanding the physiology of gut bacteria and their interactions with the host. However, construction of high-quality libraries with uniform representation can be challenging. In this review, we survey various strategies for barcoded library construction, including transposition systems, methods of transposon delivery, optimal library size, and transconjugant selection schemes. We discuss the advantages and limitations of each approach, as well as factors to consider when selecting a strategy. In addition, we highlight experimental and computational advances in arraying condensed libraries from mutant pools. We focus on examples of successful library construction in gut bacteria and their application to gene function studies and drug discovery. Given the need for understanding gene function and organization in gut bacteria, we provide a comprehensive guide for researchers to construct randomly barcoded transposon mutant libraries.

Randomly barcoded transposon mutant libraries for gut commensals II: Applying libraries for functional genetics.

The critical role of the intestinal microbiota in human health and disease is well recognized. Nevertheless, there are still large gaps in our understanding of the functions and mechanisms encoded in the genomes of most members of the gut microbiota. Genome-scale libraries of transposon mutants are a powerful tool to help us address this gap. Recent advances in barcoded transposon mutagenesis have dramatically lowered the cost of mutant fitness determination in hundreds of in vitro and in vivo experimental conditions. In an accompanying review, we discuss recent advances and caveats for the construction of pooled and arrayed barcoded transposon mutant libraries in human gut commensals. In this review, we discuss how these libraries can be used across a wide range of applications, the technical aspects involved, and expectations for such screens.

Systematic analysis of drug combinations against Gram-positive bacteria.

Drug combinations can expand options for antibacterial therapies but have not been systematically tested in Gram-positive species. We profiled ~8,000 combinations of 65 antibacterial drugs against the model species Bacillus subtilis and two prominent pathogens, Staphylococcus aureus and Streptococcus pneumoniae. Thereby, we recapitulated previously known drug interactions, but also identified ten times more novel interactions in the pathogen S. aureus, including 150 synergies. We showed that two synergies were equally effective against multidrug-resistant S. aureus clinical isolates in vitro and in vivo. Interactions were largely species-specific and synergies were distinct from those of Gram-negative species, owing to cell surface and drug uptake differences. We also tested 2,728 combinations of 44 commonly prescribed non-antibiotic drugs with 62 drugs with antibacterial activity against S. aureus and identified numerous antagonisms that might compromise the efficacy of antimicrobial therapies. We identified even more synergies and showed that the anti-aggregant ticagrelor synergized with cationic antibiotics by modifying the surface charge of S. aureus. All data can be browsed in an interactive interface ( https://apps.embl.de/combact/ ).

A pathogen-specific isotope tracing approach reveals metabolic activities and fluxes of intracellular Salmonella.

Pathogenic bacteria proliferating inside mammalian host cells need to rapidly adapt to the intracellular environment. How they achieve this and scavenge essential nutrients from the host has been an open question due to the difficulties in distinguishing between bacterial and host metabolites in situ. Here, we capitalized on the inability of mammalian cells to metabolize mannitol to develop a stable isotopic labeling approach to track Salmonella enterica metabolites during intracellular proliferation in host macrophage and epithelial cells. By measuring label incorporation into Salmonella metabolites with liquid chromatography-mass spectrometry (LC-MS), and combining it with metabolic modeling, we identify relevant carbon sources used by Salmonella, uncover routes of their metabolization, and quantify relative reaction rates in central carbon metabolism. Our results underline the importance of the Entner-Doudoroff pathway (EDP) and the phosphoenolpyruvate carboxylase for intracellularly proliferating Salmonella. More broadly, our metabolic labeling strategy opens novel avenues for understanding the metabolism of pathogens inside host cells.

Consistency across multi-omics layers in a drug-perturbed gut microbial community.

Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.

D-amino acids signal a stress-dependent run-away response in Vibrio cholerae.

To explore favourable niches while avoiding threats, many bacteria use a chemotaxis navigation system. Despite decades of studies on chemotaxis, most signals and sensory proteins are still unknown. Many bacterial species release D-amino acids to the environment; however, their function remains largely unrecognized. Here we reveal that D-arginine and D-lysine are chemotactic repellent signals for the cholera pathogen Vibrio cholerae. These D-amino acids are sensed by a single chemoreceptor MCPDRK co-transcribed with the racemase enzyme that synthesizes them under the control of the stress-response sigma factor RpoS. Structural characterization of this chemoreceptor bound to either D-arginine or D-lysine allowed us to pinpoint the residues defining its specificity. Interestingly, the specificity for these D-amino acids appears to be restricted to those MCPDRK orthologues transcriptionally linked to the racemase. Our results suggest that D-amino acids can shape the biodiversity and structure of complex microbial communities under adverse conditions.

The New Microbiology: an international lecture course on the island of Spetses.

In September 2022, an international summer course entitled 'The new microbiology' took place in Greece, on the island of Spetses. The organizers aimed to highlight the spectacular advances and the renaissance occurring in Microbiology, driven by developments in genomics, proteomics, imaging techniques, and bioinformatics. Combinations of these advances allow for single cell analyses, rapid and relatively inexpensive metagenomic and transcriptomic data analyses and comparisons, visualization of previously unsuspected mechanisms, and large-scale studies. A 'New Microbiology' is emerging which allows studies that address the critical roles of microbes in health and disease, in humans, animals, and the environment. The concept of one health is now transforming microbiology. The goal of the course was to discuss all these topics with members of the new generation of microbiologists all of whom were highly motivated and fully receptive.

Unravelling metabolic cross-feeding in a yeast-bacteria community using 13 C-based proteomics.

Cross-feeding is fundamental to the diversity and function of microbial communities. However, identification of cross-fed metabolites is often challenging due to the universality of metabolic and biosynthetic intermediates. Here, we use 13 C isotope tracing in peptides to elucidate cross-fed metabolites in co-cultures of Saccharomyces cerevisiae and Lactococcus lactis. The community was grown on lactose as the main carbon source with either glucose or galactose fraction of the molecule labelled with 13 C. Data analysis allowing for the possible mass-shifts yielded hundreds of peptides for which we could assign both species identity and labelling degree. The labelling pattern showed that the yeast utilized galactose and, to a lesser extent, lactic acid shared by L. lactis as carbon sources. While the yeast provided essential amino acids to the bacterium as expected, the data also uncovered a complex pattern of amino acid exchange. The identity of the cross-fed metabolites was further supported by metabolite labelling in the co-culture supernatant, and by diminished fitness of a galactose-negative yeast mutant in the community. Together, our results demonstrate the utility of 13 C-based proteomics for uncovering microbial interactions.

2FAST2Q: a general-purpose sequence search and counting program for FASTQ files.

Background: The increasingly widespread use of next generation sequencing protocols has brought the need for the development of user-friendly raw data processing tools. Here, we explore 2FAST2Q, a versatile and intuitive standalone program capable of extracting and counting feature occurrences in FASTQ files. Despite 2FAST2Q being previously described as part of a CRISPRi-seq analysis pipeline, in here we further elaborate on the program's functionality, and its broader applicability and functions. Methods: 2FAST2Q is built in Python, with published standalone executables in Windows MS, MacOS, and Linux. It has a familiar user interface, and uses an advanced custom sequence searching algorithm. Results: Using published CRISPRi datasets in which Escherichia coli and Mycobacterium tuberculosis gene essentiality, as well as host-cell sensitivity towards SARS-CoV2 infectivity were tested, we demonstrate that 2FAST2Q efficiently recapitulates published output in read counts per provided feature. We further show that 2FAST2Q can be used in any experimental setup that requires feature extraction from raw reads, being able to quickly handle Hamming distance based mismatch alignments, nucleotide wise Phred score filtering, custom read trimming, and sequence searching within a single program. Moreover, we exemplify how different FASTQ read filtering parameters impact downstream analysis, and suggest a default usage protocol. 2FAST2Q is easier to use and faster than currently available tools, efficiently processing not only CRISPRi-seq / random-barcode sequencing datasets on any up-to-date laptop, but also handling the advanced extraction of de novo features from FASTQ files. We expect that 2FAST2Q will not only be useful for people working in microbiology but also for other fields in which amplicon sequencing data is generated. 2FAST2Q is available as an executable file for all current operating systems without installation and as a Python3 module on the PyPI repository (available at https://veeninglab.com/2fast2q).

Transient Glycolytic Complexation of Arsenate Enhances Resistance in the Enteropathogen Vibrio cholerae.

The ubiquitous presence of toxic arsenate (AsV) in the environment has raised mechanisms of resistance in all living organisms. Generally, bacterial detoxification of AsV relies on its reduction to arsenite (AsIII) by ArsC, followed by the export of AsIII by ArsB. However, how pathogenic species resist this metalloid remains largely unknown. Here, we found that Vibrio cholerae, the etiologic agent of the diarrheal disease cholera, outcompetes other enteropathogens when grown on millimolar concentrations of AsV. To do so, V. cholerae uses, instead of ArsCB, the AsV-inducible vc1068-1071 operon (renamed var for vibrio arsenate resistance), which encodes the arsenate repressor ArsR, an alternative glyceraldehyde-3-phosphate dehydrogenase, a putative phosphatase, and the AsV transporter ArsJ. In addition to Var, V. cholerae induces oxidative stress-related systems to counter reactive oxygen species (ROS) production caused by intracellular AsV. Characterization of the var mutants suggested that these proteins function independently from one another and play critical roles in preventing deleterious effects on the cell membrane potential and growth derived from the accumulation AsV. Mechanistically, we demonstrate that V. cholerae complexes AsV with the glycolytic intermediate 3-phosphoglycerate into 1-arseno-3-phosphoglycerate (1As3PG). We further show that 1As3PG is not transported outside the cell; instead, it is subsequently dissociated to enable extrusion of free AsV through ArsJ. Collectively, we propose the formation of 1As3PG as a transient metabolic storage of AsV to curb the noxious effect of free AsV. This study advances our understanding of AsV resistance in bacteria and underscores new points of vulnerability that might be an attractive target for antimicrobial interventions. IMPORTANCE Even though resistance to arsenate has been extensively investigated in environmental bacteria, how enteric pathogens tolerate this toxic compound remains unknown. Here, we found that the cholera pathogen V. cholerae exhibits increased resistance to arsenate compared to closely related enteric pathogens. Such resistance is promoted not by ArsC-dependent reduction of arsenate to arsenite but by an operon encoding an arsenate transporter (ArsJ), an alternative glyceraldehyde 3-phosphate dehydrogenase (VarG), and a putative, uncharacterized phosphatase (VarH). Mechanistically, we demonstrate that V. cholerae detoxifies arsenate by complexing it with the glycolytic intermediate 3-phosphoglycerate into 1-arseno-3-phosphoglycerate (1As3PG). 1As3PG is not transported outside the cell; instead, it is subsequently dissociated by VarH to enable extrusion of free arsenate through ArsJ. Collectively, this study proposes a novel mechanism for arsenate detoxification, entirely independent of arsenate reduction and arsenite extrusion, that enhances V. cholerae resistance to this metalloid compared to other enteric pathogens.

Bacterial retrons encode phage-defending tripartite toxin-antitoxin systems.

Retrons are prokaryotic genetic retroelements encoding a reverse transcriptase that produces multi-copy single-stranded DNA1 (msDNA). Despite decades of research on the biosynthesis of msDNA2, the function and physiological roles of retrons have remained unknown. Here we show that Retron-Sen2 of Salmonella enterica serovar Typhimurium encodes an accessory toxin protein, STM14_4640, which we renamed as RcaT. RcaT is neutralized by the reverse transcriptase-msDNA antitoxin complex, and becomes active upon perturbation of msDNA biosynthesis. The reverse transcriptase is required for binding to RcaT, and the msDNA is required for the antitoxin activity. The highly prevalent RcaT-containing retron family constitutes a new type of tripartite DNA-containing toxin-antitoxin system. To understand the physiological roles of such toxin-antitoxin systems, we developed toxin activation-inhibition conjugation (TAC-TIC), a high-throughput reverse genetics approach that identifies the molecular triggers and blockers of toxin-antitoxin systems. By applying TAC-TIC to Retron-Sen2, we identified multiple trigger and blocker proteins of phage origin. We demonstrate that phage-related triggers directly modify the msDNA, thereby activating RcaT and inhibiting bacterial growth. By contrast, prophage proteins circumvent retrons by directly blocking RcaT. Consistently, retron toxin-antitoxin systems act as abortive infection anti-phage defence systems, in line with recent reports3,4. Thus, RcaT retrons are tripartite DNA-regulated toxin-antitoxin systems, which use the reverse transcriptase-msDNA complex both as an antitoxin and as a sensor of phage protein activities.

Early midcell localization of Escherichia coli PBP4 supports the function of peptidoglycan amidases.

Insertion of new material into the Escherichia coli peptidoglycan (PG) sacculus between the cytoplasmic membrane and the outer membrane requires a well-organized balance between synthetic and hydrolytic activities to maintain cell shape and avoid lysis. Since most bacteria carry multiple enzymes carrying the same type of PG hydrolytic activity, we know little about the specific function of given enzymes. Here we show that the DD-carboxy/endopeptidase PBP4 localizes in a PBP1A/LpoA and FtsEX dependent fashion at midcell during septal PG synthesis. Midcell localization of PBP4 requires its non-catalytic domain 3 of unknown function, but not the activity of PBP4 or FtsE. Microscale thermophoresis with isolated proteins shows that PBP4 interacts with NlpI and the FtsEX-interacting protein EnvC, an activator of amidases AmiA and AmiB, which are needed to generate denuded glycan strands to recruit the initiator of septal PG synthesis, FtsN. The domain 3 of PBP4 is needed for the interaction with NlpI and EnvC, but not PBP1A or LpoA. In vivo crosslinking experiments confirm the interaction of PBP4 with PBP1A and LpoA. We propose that the interaction of PBP4 with EnvC, whilst not absolutely necessary for mid-cell recruitment of either protein, coordinates the activities of PBP4 and the amidases, which affects the formation of denuded glycan strands that attract FtsN. Consistent with this model, we found that the divisome assembly at midcell was premature in cells lacking PBP4, illustrating how the complexity of interactions affect the timing of cell division initiation.

Bioactivity assessment of natural compounds using machine learning models trained on target similarity between drugs.

Natural compounds constitute a rich resource of potential small molecule therapeutics. While experimental access to this resource is limited due to its vast diversity and difficulties in systematic purification, computational assessment of structural similarity with known therapeutic molecules offers a scalable approach. Here, we assessed functional similarity between natural compounds and approved drugs by combining multiple chemical similarity metrics and physicochemical properties using a machine-learning approach. We computed pairwise similarities between 1410 drugs for training classification models and used the drugs shared protein targets as class labels. The best performing models were random forest which gave an average area under the ROC of 0.9, Matthews correlation coefficient of 0.35, and F1 score of 0.33, suggesting that it captured the structure-activity relation well. The models were then used to predict protein targets of circa 11k natural compounds by comparing them with the drugs. This revealed therapeutic potential of several natural compounds, including those with support from previously published sources as well as those hitherto unexplored. We experimentally validated one of the predicted pair's activities, viz., Cox-1 inhibition by 5-methoxysalicylic acid, a molecule commonly found in tea, herbs and spices. In contrast, another natural compound, 4-isopropylbenzoic acid, with the highest similarity score when considering most weighted similarity metric but not picked by our models, did not inhibit Cox-1. Our results demonstrate the utility of a machine-learning approach combining multiple chemical features for uncovering protein binding potential of natural compounds.

High-throughput functional characterization of protein phosphorylation sites in yeast.

Phosphorylation is a critical post-translational modification involved in the regulation of almost all cellular processes. However, fewer than 5% of thousands of recently discovered phosphosites have been functionally annotated. In this study, we devised a chemical genetic approach to study the functional relevance of phosphosites in Saccharomyces cerevisiae. We generated 474 yeast strains with mutations in specific phosphosites that were screened for fitness in 102 conditions, along with a gene deletion library. Of these phosphosites, 42% exhibited growth phenotypes, suggesting that these are more likely functional. We inferred their function based on the similarity of their growth profiles with that of gene deletions and validated a subset by thermal proteome profiling and lipidomics. A high fraction exhibited phenotypes not seen in the corresponding gene deletion, suggestive of a gain-of-function effect. For phosphosites conserved in humans, the severity of the yeast phenotypes is indicative of their human functional relevance. This high-throughput approach allows for functionally characterizing individual phosphosites at scale.

Unravelling the collateral damage of antibiotics on gut bacteria.

Antibiotics are used to fight pathogens but also target commensal bacteria, disturbing the composition of gut microbiota and causing dysbiosis and disease1. Despite this well-known collateral damage, the activity spectrum of different antibiotic classes on gut bacteria remains poorly characterized. Here we characterize further 144 antibiotics from a previous screen of more than 1,000 drugs on 38 representative human gut microbiome species2. Antibiotic classes exhibited distinct inhibition spectra, including generation dependence for quinolones and phylogeny independence for ß-lactams. Macrolides and tetracyclines, both prototypic bacteriostatic protein synthesis inhibitors, inhibited nearly all commensals tested but also killed several species. Killed bacteria were more readily eliminated from in vitro communities than those inhibited. This species-specific killing activity challenges the long-standing distinction between bactericidal and bacteriostatic antibiotic classes and provides a possible explanation for the strong effect of macrolides on animal3-5 and human6,7 gut microbiomes. To mitigate this collateral damage of macrolides and tetracyclines, we screened for drugs that specifically antagonized the antibiotic activity against abundant Bacteroides species but not against relevant pathogens. Such antidotes selectively protected Bacteroides species from erythromycin treatment in human-stool-derived communities and gnotobiotic mice. These findings illluminate the activity spectra of antibiotics in commensal bacteria and suggest strategies to circumvent their adverse effects on the gut microbiota.

Transcriptional and Post-Transcriptional Polar Effects in Bacterial Gene Deletion Libraries.

Single-gene deletions can affect the expression levels of other genes in the same operon in bacterial genomes. Here, we used proteomics for 133 Escherichia coli gene deletion mutants and transcriptome sequencing (RNA-seq) data from 71 mutants to probe the extent of transcriptional and post-transcriptional effects of gene deletions in operons. Transcriptional effects were common on genes located downstream of the deletion and were consistent across all operon members, with nearly 40% of operons showing greater than 2-fold up- or downregulation. Surprisingly, we observed an additional post-transcriptional effect that leads to the downregulation of the gene located directly downstream of the targeted gene. This effect was correlated with their intergenic distance, despite the ribosome binding site of the gene downstream remaining intact during library construction. Overall, the data presented can guide future library construction and highlight the importance of follow-up experiments for assessing direct effects of single-gene deletions in operons. IMPORTANCE Single-gene deletion libraries have allowed genome-wide characterization of gene function and interactions. While each mutant intends to disrupt the function of a single gene, it can unintentionally target other genes, such as those located in the same operon as the deletion. The extent to which such polar effects occur in deletion libraries has not been assessed. In this work, we use proteomics and transcriptomics data to show that transcript level changes lead to nearly 40% of deletions in operons affecting the protein levels of genes located downstream by at least 2-fold. Furthermore, we observed a post-transcriptional effect on the gene located directly downstream of the deletion. These results can guide the design of future gene deletion libraries and emphasizes the importance of follow-up work when linking genotypes to phenotypes.

Bioaccumulation of therapeutic drugs by human gut bacteria.

Bacteria in the gut can modulate the availability and efficacy of therapeutic drugs. However, the systematic mapping of the interactions between drugs and bacteria has only started recently1 and the main underlying mechanism proposed is the chemical transformation of drugs by microorganisms (biotransformation). Here we investigated the depletion of 15 structurally diverse drugs by 25 representative strains of gut bacteria. This revealed 70 bacteria-drug interactions, 29 of which had not to our knowledge been reported before. Over half of the new interactions can be ascribed to bioaccumulation; that is, bacteria storing the drug intracellularly without chemically modifying it, and in most cases without the growth of the bacteria being affected. As a case in point, we studied the molecular basis of bioaccumulation of the widely used antidepressant duloxetine by using click chemistry, thermal proteome profiling and metabolomics. We find that duloxetine binds to several metabolic enzymes and changes the metabolite secretion of the respective bacteria. When tested in a defined microbial community of accumulators and non-accumulators, duloxetine markedly altered the composition of the community through metabolic cross-feeding. We further validated our findings in an animal model, showing that bioaccumulating bacteria attenuate the behavioural response of Caenorhabditis elegans to duloxetine. Together, our results show that bioaccumulation by gut bacteria may be a common mechanism that alters drug availability and bacterial metabolism, with implications for microbiota composition, pharmacokinetics, side effects and drug responses, probably in an individual manner.

Global mapping of Salmonella enterica-host protein-protein interactions during infection.

Intracellular bacterial pathogens inject effector proteins to hijack host cellular processes and promote their survival and proliferation. To systematically map effector-host protein-protein interactions (PPIs) during infection, we generated a library of 32 Salmonella enterica serovar Typhimurium (STm) strains expressing chromosomally encoded affinity-tagged effectors and quantified PPIs in macrophages and epithelial cells. We identified 446 effector-host PPIs, 25 of which were previously described, and validated 13 by reciprocal co-immunoprecipitation. While effectors converged on the same host cellular processes, most had multiple targets, which often differed between cell types. We demonstrate that SseJ, SseL, and SifA modulate cholesterol accumulation at the Salmonella-containing vacuole (SCV) partially via the cholesterol transporter Niemann-Pick C1 protein. PipB recruits the organelle contact site protein PDZD8 to the SCV, and SteC promotes actin bundling by phosphorylating formin-like proteins. This study provides a method for probing host-pathogen PPIs during infection and a resource for interrogating STm effector mechanisms.