Genome-scale identification of Legionella pneumophila effectors using a machine learning approach

Modulation of host ATP levels by secreted bacterial effectors

Adenosine 5'-triphosphate (ATP) is the currency of energy in cells; it plays essential roles in virtually all cellular processes, ranging from basic metabolism to signaling in development and disease. The opportunistic bacterial pathogen Legionella pneumophila utilizes the Dot/Icm type IV secretion system to deliver over 300 effectors into host cells, some of which utilize ATP to perform biochemical reactions catalyzed by their unique enzymatic activities. However, whether L. pneumophila directly regulates ATP level in host cells is unknown. Here, we discover that the Dot/Icm substrate Ceg14 (Lpg0437, a.k.a. SidL) is an ATP/dATPase, which after being activated by the host protein actin, efficiently converts ATP and dATP into adenosine and deoxyadenosine monophosphate, respectively by a mechanism that requires its S-HxxxE (x, any amino acid) motif. The activity of Ceg14 is regulated by its metaeffector AnkJ (Lpg0436, a.k.a. LegA11), which inhibits its ATPase activity via direct protein-protein interactions. Ceg14 and AnkJ impose temporal regulation of ATP levels in L. pneumophila-infected cells. Our results demonstrate that L. pneumophila modulates the energy level of host cells to create an environment permissive for its growth.

Contrastive-learning of language embedding and biological features for cross modality encoding and effector prediction

Identifying and characterizing virulence proteins secreted by Gram-negative bacteria are fundamental for deciphering microbial pathogenicity as well as aiding the development of therapeutic strategies. Effector predictors utilizing pre-trained protein language models (PLMs) have shown sound performance by leveraging extensive evolutionary and sequential protein features. However, the accuracy and sensitivity of effector prediction remain challenging. Here, we introduce a model named Contrastive-learning of Language Embedding and Biological Features (CLEF) leveraging contrastive learning to integrate PLM representations with supplementary biological features. Biologically information is captured in learned contextualized embeddings to yield meaningful representations. With cross-modality biological features, CLEF outperforms state-of-the-art (SOTA) models in predicting type III, type IV, and type VI secreted effectors (T3SEs/T4SEs/T6SEs) in enteric pathogens. All experimentally verified effectors in Enterohemorrhagic Escherichia coli and 41 of 43 experimentally verified T3SEs of Salmonella Typhimurium are recognized. Moreover, 12 predicted T3SEs and 11 predicted T6SEs are validated by extensive experiments in Edwardsiella piscicida. Furthermore, integrating omics data via CLEF framework enhances protein representations to illustrate effector-effector interactions and determine in vivo colonization-essential genes. Collectively, CLEF provides a blueprint to bridge the gap between in silico PLM's capacity and experimental biological information to fulfill complicated tasks.

Diverse genetic conflicts mediated by molecular mimicry and computational approaches to detect them

In genetic conflicts between intergenomic and selfish elements, driver and killer elements achieve biased survival, replication, or transmission over sensitive and targeted elements through a wide range of molecular mechanisms, including mimicry. Driving mechanisms manifest at all organismal levels, from the biased propagation of individual genes, as demonstrated by transposable elements, to the biased transmission of genomes, as illustrated by viruses, to the biased transmission of cell lineages, as in cancer. Targeted genomes are vulnerable to molecular mimicry through the conserved motifs they use for their own signaling and regulation. Mimicking these motifs enables an intergenomic or selfish element to control core target processes, and can occur at the sequence, structure, or functional level. Molecular mimicry was first appreciated as an important phenomenon more than twenty years ago. Modern genomics technologies, databases, and machine learning approaches offer tremendous potential to study the distribution of molecular mimicry across genetic conflicts in nature. Here, we explore the theoretical expectations for molecular mimicry between conflicting genomes, the trends in molecular mimicry mechanisms across known genetic conflicts, and outline how new examples can be gleaned from population genomic datasets. We discuss how mimics involving short sequence-based motifs or gene duplications can evolve convergently from new mutations. Whereas, processes that involve divergent domains or fully-folded structures occur among genomes by horizontal gene transfer. These trends are largely based on a small number of organisms and should be reevaluated in a general, phylogenetically independent framework. Currently, publicly available databases can be mined for genotypes driving non-Mendelian inheritance patterns, epistatic interactions, and convergent protein structures. A subset of these conflicting elements may be molecular mimics. We propose approaches for detecting genetic conflict and molecular mimicry from these datasets.

The Passage of Chaperonins to Extracellular Locations in Legionella pneumophila Requires a Functional Dot/Icm System

HtpB, the chaperonin of the bacterial pathogen L. pneumophila, is found in extracellular locations, even the cytoplasm of host cells. Although chaperonins have an essential cytoplasmic function in protein folding, HtpB exits the cytoplasm to perform extracellular virulence-related functions that support L. pneumophila's lifestyle. The mechanism by which HtpB reaches extracellular locations is not currently understood. To address this experimental gap, immunoelectron microscopy, trypsin-accessibility assays, and cell fractionation were used to localize HtpB in various L. pneumophila secretion mutants. Dot/Icm type IV secretion mutants displayed less surface-exposed HtpB and more periplasmic HtpB than parent strains. The analysis of periplasmic extracts and outer membrane vesicles of these mutants, where HtpB co-localized with bona fide periplasmic proteins, confirmed the elevated levels of periplasmic HtpB. Genetic complementation of the mutants recovered parent strain levels of surface-exposed and periplasmic HtpB. The export of GSK-tagged HtpB into the cytoplasm of infected cells was also Dot/Icm-dependent. The translocating role of the Dot/Icm system was not specific for HtpB because GroEL, the chaperonin of Escherichia coli, was found at the cell surface and accumulated in the periplasm of Dot mutants when expressed in L. pneumophila. These findings establish that a functional Dot/Icm system is required for HtpB to reach extracellular locations, but the mechanism by which cytoplasmic HtpB reaches the periplasm remains partially unidentified.

Global atlas of predicted functional domains in Legionella pneumophila Dot/Icm translocated effectors

Legionella pneumophila utilizes the Dot/Icm type IVB secretion system to deliver hundreds of effector proteins inside eukaryotic cells to ensure intracellular replication. Our understanding of the molecular functions of the largest pathogenic arsenal known to the bacterial world remains incomplete. By leveraging advancements in 3D protein structure prediction, we provide a comprehensive structural analysis of 368 L. pneumophila effectors, representing a global atlas of predicted functional domains summarized in a database ( https://pathogens3d.org/legionella-pneumophila ). Our analysis identified 157 types of diverse functional domains in 287 effectors, including 159 effectors with no prior functional annotations. Furthermore, we identified 35 cryptic domains in 30 effector models that have no similarity with experimentally structurally characterized proteins, thus, hinting at novel functionalities. Using this analysis, we demonstrate the activity of thirteen functional domains, including three cryptic domains, predicted in L. pneumophila effectors to cause growth defects in the Saccharomyces cerevisiae model system. This illustrates an emerging strategy of exploring synergies between predictions and targeted experimental approaches in elucidating novel effector activities involved in infection.

Legionella pneumophila, a Rosetta stone to understanding bacterial pathogenesis

Legionella pneumophila is an environmentally acquired pathogen that causes respiratory disease in humans. While the discovery of L. pneumophila is relatively recent compared to other bacterial pathogens, over the past 50 years, L. pneumophila has emerged as a powerhouse for studying host-pathogen interactions. In its natural habitat of fresh water, L. pneumophila interacts with a diverse array of protozoan hosts and readily evolve to expand their host range. This has led to the accumulation of the most extensive arsenal of secreted virulence factors described for a bacterial pathogen and their ability to infect humans. Within amoebae and human alveolar macrophages, the bacteria replicate within specialized membrane-bound compartments, establishing L. pneumophila as a model for studying intracellular vacuolar pathogens. In contrast, the virulence factors required for intracellular replication are specifically tailored to individual host cells types, allowing the pathogen to adapt to variation between disparate niches. The broad host range of this pathogen, combined with the extensive diversity and genome plasticity across the Legionella genus, has thus established this bacterium as an archetype to interrogate pathogen evolution, functional genomics, and ecology. In this review, we highlight the features of Legionella that establish them as a versatile model organism, new paradigms in bacteriology and bacterial pathogenesis resulting from the study of Legionella, as well as current and future questions that will undoubtedly expand our understanding of the complex and intricate biology of the microbial world.

A comprehensive two-hybrid analysis to explore the Legionella pneumophila effector-effector interactome

Legionella pneumophila uses over 300 translocated effector proteins to rewire host cells during infection and create a replicative niche for intracellular growth. To date, several studies have identified L. pneumophila effectors that indirectly and directly regulate the activity of other effectors, providing an additional layer of regulatory complexity. Among these are "metaeffectors," a special class of effectors that regulate the activity of other effectors once inside the host. A defining feature of metaeffectors is direct, physical interaction with a target effector. Metaeffector identification, to date, has depended on phenotypes in heterologous systems and experimental serendipity. Using a multiplexed, recombinant barcode-based yeast two-hybrid technology we screened for protein-protein interactions among all L. pneumophila effectors and 28 components of the Dot/Icm type IV secretion system (>167,000 protein combinations). Of the 52 protein interactions identified by this approach, 44 are novel protein interactions, including 10 novel effector-effector interactions (doubling the number of known effector-effector interactions).

IMPORTANCE

Secreted bacterial effector proteins are typically viewed as modulators of host activity, entering the host cytosol to physically interact with and modify the activity of one or more host proteins in support of infection. A growing body of evidence suggests that a subset of effectors primarily function to modify the activities of other effectors inside the host. These "effectors of effectors" or metaeffectors are often identified through experimental serendipity during the study of canonical effector function against the host. We previously performed the first global effector-wide genetic interaction screen for metaeffectors within the arsenal of Legionella pneumophila, an intracellular bacterial pathogen with over 300 effectors. Here, using a high-throughput, scalable methodology, we present the first global interaction network of physical interactions between L. pneumophila effectors. This data set serves as a complementary resource to identify and understand both the scope and nature of non-canonical effector activity within this important human pathogen.

T4SEpp: A pipeline integrating protein language models to predict bacterial type IV secreted effectors

Many pathogenic bacteria use type IV secretion systems (T4SSs) to deliver effectors (T4SEs) into the cytoplasm of eukaryotic cells, causing diseases. The identification of effectors is a crucial step in understanding the mechanisms of bacterial pathogenicity, but this remains a major challenge. In this study, we used the full-length embedding features generated by six pre-trained protein language models to train classifiers predicting T4SEs and compared their performance. We integrated three modules into a model called T4SEpp. The first module searched for full-length homologs of known T4SEs, signal sequences, and effector domains; the second module fine-tuned a machine learning model using data for a signal sequence feature; and the third module used the three best-performing pre-trained protein language models. T4SEpp outperformed other state-of-the-art (SOTA) software tools, achieving ∼0.98 accuracy at a high specificity of ∼0.99, based on the assessment of an independent validation dataset. T4SEpp predicted 13 T4SEs from Helicobacter pylori, including the well-known CagA and 12 other potential ones, among which eleven could potentially interact with human proteins. This suggests that these potential T4SEs may be associated with the pathogenicity of H. pylori. Overall, T4SEpp provides a better solution to assist in the identification of bacterial T4SEs and facilitates studies of bacterial pathogenicity. T4SEpp is freely accessible at https://bis.zju.edu.cn/T4SEpp.

The T4bSS of Legionella features a two-step secretion pathway with an inner membrane intermediate for secretion of transmembrane effectors

To promote intracellular survival and infection, Legionella spp. translocate hundreds of effector proteins into eukaryotic host cells using a type IV b protein secretion system (T4bSS). T4bSS are well known to translocate soluble as well as transmembrane domain-containing effector proteins (TMD-effectors) but the mechanisms of secretion are still poorly understood. Herein we investigated the secretion of hydrophobic TMD-effectors, of which about 80 were previously reported to be encoded by L. pneumophila. A proteomic analysis of fractionated membranes revealed that TMD-effectors are targeted to and inserted into the bacterial inner membranes of L. pneumophila independent of the presence of a functional T4bSS. While the T4bSS chaperones IcmS and IcmW were critical for secretion of all tested TMD-effectors, they did not influence inner membrane targeting of these proteins. As for soluble effector proteins, translocation of all investigated TMD-effectors depended on a C-terminal secretion signal. A deeper analysis of the TMD-effector SidF showed that this signal needed to be presented towards the cytoplasmic side of the inner membrane and that a small periplasmic loop was required for efficient translocation. We propose that strongly hydrophobic TMD-effectors are secreted in a two-step secretion process: Initially, an inner membrane intermediate is formed, that is extracted towards the cytoplasmic side, possibly by the help of the type IV coupling protein complex and subsequently secreted into eukaryotic host cells by the T4bSS core complex. Overall, our study highlights the amazing versatility of T4bSS to secrete soluble and TMD-effectors from different subcellular locations of the bacterial cell.

Genetic evidence for a regulated cysteine protease catalytic triad in LegA7, a Legionella pneumophila protein that impinges on a stress response pathway

Legionella pneumophila grows within membrane-bound vacuoles in phylogenetically diverse hosts. Intracellular growth requires the function of the Icm/Dot type-IVb secretion system, which translocates more than 300 proteins into host cells. A screen was performed to identify L. pneumophila proteins that stimulate mitogen-activated protein kinase (MAPK) activation, using Icm/Dot translocated proteins ectopically expressed in mammalian cells. In parallel, a second screen was performed to identify L. pneumophila proteins expressed in yeast that cause growth inhibition in MAPK pathway-stimulatory high-osmolarity medium. LegA7 was shared in both screens, a protein predicted to be a member of the bacterial cysteine protease family that has five carboxyl-terminal ankyrin repeats. Three conserved residues in the predicted catalytic triad of LegA7 were mutated. These mutations abolished the ability of LegA7 to inhibit yeast growth. To identify other residues important for LegA7 function, a generalizable selection strategy in yeast was devised to isolate mutants that have lost function and no longer cause growth inhibition on a high-osmolarity medium. Mutations were isolated in the two carboxyl-terminal ankyrin repeats, as well as an inter-domain region located between the cysteine protease domain and the ankyrin repeats. These mutations were predicted by AlphaFold modeling to localize to the face opposite from the catalytic site, arguing that they interfere with the positive regulation of the catalytic activity. Based on our data, we present a model in which LegA7 harbors a cysteine protease domain with an inter-domain and two carboxyl-terminal ankyrin repeat regions that modulate the function of the catalytic domain.

IMPORTANCE

Legionella pneumophila grows in a membrane-bound compartment in macrophages during disease. Construction of the compartment requires a dedicated secretion system that translocates virulence proteins into host cells. One of these proteins, LegA7, is shown to activate a stress response pathway in host cells called the mitogen-activated protein kinase (MAPK) pathway. The effects on the mammalian MAPK pathway were reconstructed in yeast, allowing the development of a strategy to identify the role of individual domains of LegA7. A domain similar to cysteine proteases is demonstrated to be critical for impinging on the MAPK pathway, and the catalytic activity of this domain is required for targeting this path. In addition, a conserved series of repeats, called ankyrin repeats, controls this activity. Data are provided that argue the interaction of the ankyrin repeats with unknown targets probably results in activation of the cysteine protease domain.

A random mutagenesis screen enriched for missense mutations in bacterial effector proteins

To remodel their hosts and escape immune defenses, many pathogens rely on large arsenals of proteins (effectors) that are delivered to the host cell using dedicated translocation machinery. Effectors hold significant insight into the biology of both the pathogens that encode them and the host pathways that they manipulate. One of the most powerful systems biology tools for studying effectors is the model organism, Saccharomyces cerevisiae. For many pathogens, the heterologous expression of effectors in yeast is growth inhibitory at a frequency much higher than housekeeping genes, an observation ascribed to targeting conserved eukaryotic proteins. Abrogation of yeast growth inhibition has been used to identify bacterial suppressors of effector activity, host targets, and functional residues and domains within effector proteins. We present here a yeast-based method for enriching for informative, in-frame, missense mutations in a pool of random effector mutants. We benchmark this approach against three effectors from Legionella pneumophila, an intracellular bacterial pathogen that injects a staggering >330 effectors into the host cell. For each protein, we show how in silico protein modeling (AlphaFold2) and missense-directed mutagenesis can be combined to reveal important structural features within effectors. We identify known active site residues within the metalloprotease RavK, the putative active site in SdbB, and previously unidentified functional motifs within the C-terminal domain of SdbA. We show that this domain has structural similarity with glycosyltransferases and exhibits in vitro activity consistent with this predicted function.

Identification of novel toxins associated with the extracellular contractile injection system using machine learning

Secretion systems play a crucial role in microbe-microbe or host-microbe interactions. Among these systems, the extracellular contractile injection system (eCIS) is a unique bacterial and archaeal extracellular secretion system that injects protein toxins into target organisms. However, the specific proteins that eCISs inject into target cells and their functions remain largely unknown. Here, we developed a machine learning classifier to identify eCIS-associated toxins (EATs). The classifier combines genetic and biochemical features to identify EATs. We also developed a score for the eCIS N-terminal signal peptide to predict EAT loading. Using the classifier we classified 2,194 genes from 950 genomes as putative EATs. We validated four new EATs, EAT14-17, showing toxicity in bacterial and eukaryotic cells, and identified residues of their respective active sites that are critical for toxicity. Finally, we show that EAT14 inhibits mitogenic signaling in human cells. Our study provides insights into the diversity and functions of EATs and demonstrates machine learning capability of identifying novel toxins. The toxins can be employed in various applications dependently or independently of eCIS.

CRISPRi functional genomics in bacteria and its application to medical and industrial research

SUMMARYFunctional genomics is the use of systematic gene perturbation approaches to determine the contributions of genes under conditions of interest. Although functional genomic strategies have been used in bacteria for decades, recent studies have taken advantage of CRISPR (clustered regularly interspaced short palindromic repeats) technologies, such as CRISPRi (CRISPR interference), that are capable of precisely modulating expression of all genes in the genome. Here, we discuss and review the use of CRISPRi and related technologies for bacterial functional genomics. We discuss the strengths and weaknesses of CRISPRi as well as design considerations for CRISPRi genetic screens. We also review examples of how CRISPRi screens have defined relevant genetic targets for medical and industrial applications. Finally, we outline a few of the many possible directions that could be pursued using CRISPR-based functional genomics in bacteria. Our view is that the most exciting screens and discoveries are yet to come.

Genetic evidence for a regulated cysteine protease catalytic triad in LegA7, a Legionella pneumophila protein that impinges on a stress response pathway

Legionella pneumophila grows within membrane-bound vacuoles in phylogenetically diverse hosts. Intracellular growth requires the function of the Icm/Dot type-IVb secretion system, which translocates more than 300 proteins into host cells. A screen was performed to identify L. pneumophila proteins that stimulate MAPK activation, using Icm/Dot translocated proteins ectopically expressed in mammalian cells. In parallel, a second screen was performed to identify L. pneumophila proteins expressed in yeast that cause growth inhibition in MAPK pathway-stimulatory high osmolarity medium. LegA7 was shared in both screens, a protein predicted to be a member of the bacterial cysteine protease family that has five carboxyl-terminal ankyrin repeats. Three conserved residues in the predicted catalytic triad of LegA7 were mutated. These mutations abolished the ability of LegA7 to inhibit yeast growth. To identify other residues important for LegA7 function, a generalizable selection strategy in yeast was devised to isolate mutants that have lost function and no longer cause growth inhibition on high osmolarity medium. Mutations were isolated in the two carboxyl-terminal ankyrin repeats, as well as an inter-domain region located between the cysteine protease domain and the ankyrin repeats. These mutations were predicted by AlphaFold modeling to localize to the face opposite from the catalytic site, arguing that they interfere with the positive regulation of the catalytic activity. Based on our data, we present a model in which LegA7 harbors a cysteine protease domain with an inter-domain and two carboxyl-terminal ankyrin repeat regions that modulate the function of the catalytic domain.

A Structural Proteome Screen Identifies Protein Mimicry in Host-Microbe Systems

Host-microbe systems are evolutionary niches that produce coevolved biological interactions and are a key component of global health. However, these systems have historically been a difficult field of biological research due to their experimental intractability. Impactful advances in global health will be obtained by leveraging in silico screens to identify genes involved in mediating interspecific interactions. These predictions will progress our understanding of these systems and lay the groundwork for future in vitro and in vivo experiments and bioengineering projects. A driver of host-manipulation and intracellular survival utilized by host-associated microbes is molecular mimicry, a critical mechanism that can occur at any level from DNA to protein structures. We applied protein structure prediction and alignment tools to explore host-associated bacterial structural proteomes for examples of protein structure mimicry. By leveraging the Legionella pneumophila proteome and its many known structural mimics, we developed and validated a screen that can be applied to virtually any host-microbe system to uncover signals of protein mimicry. These mimics represent candidate proteins that mediate host interactions in microbial proteomes. We successfully applied this screen to other microbes with demonstrated effects on global health, Helicobacter pylori and Wolbachia , identifying protein mimic candidates in each proteome. We discuss the roles these candidates may play in important Wolbachia -induced phenotypes and show that Wobachia infection can partially rescue the loss of one of these factors. This work demonstrates how a genome-wide screen for candidates of host-manipulation and intracellular survival offers an opportunity to identify functionally important genes in host-microbe systems.

Machine Learning and Deep Learning in Synthetic Biology: Key Architectures, Applications, and Challenges

Machine learning (ML), particularly deep learning (DL), has made rapid and substantial progress in synthetic biology in recent years. Biotechnological applications of biosystems, including pathways, enzymes, and whole cells, are being probed frequently with time. The intricacy and interconnectedness of biosystems make it challenging to design them with the desired properties. ML and DL have a synergy with synthetic biology. Synthetic biology can be employed to produce large data sets for training models (for instance, by utilizing DNA synthesis), and ML/DL models can be employed to inform design (for example, by generating new parts or advising unrivaled experiments to perform). This potential has recently been brought to light by research at the intersection of engineering biology and ML/DL through achievements like the design of novel biological components, best experimental design, automated analysis of microscopy data, protein structure prediction, and biomolecular implementations of ANNs (Artificial Neural Networks). I have divided this review into three sections. In the first section, I describe predictive potential and basics of ML along with myriad applications in synthetic biology, especially in engineering cells, activity of proteins, and metabolic pathways. In the second section, I describe fundamental DL architectures and their applications in synthetic biology. Finally, I describe different challenges causing hurdles in the progress of ML/DL and synthetic biology along with their solutions.

The Wolbachia WalE1 effector alters Drosophila endocytosis

The most common intracellular bacterial infection is Wolbachia pipientis, a microbe that manipulates host reproduction and is used in control of insect vectors. Phenotypes induced by Wolbachia have been studied for decades and range from sperm-egg incompatibility to male killing. How Wolbachia alters host biology is less well understood. Previously, we characterized the first Wolbachia effector-WalE1, which encodes an alpha-synuclein domain at the N terminus. Purified WalE1 sediments with and bundles actin and when heterologously expressed in flies, increases Wolbachia titer in the developing oocyte. In this work, we first identify the native expression of WalE1 by Wolbachia infecting both fly cells and whole animals. WalE1 appears as aggregates in the host cell cytosol. We next show that WalE1 co-immunoprecipitates with the host protein Past1, although might not directly interact with it, and that WalE1 manipulates host endocytosis. Yeast expressing WalE1 show deficiency in uptake of FM4-64 dye, and flies harboring mutations in Past1 or overexpressing WalE1 are sensitive to AgNO3, a hallmark of endocytosis defects. We also show that flies expressing WalE1 suffer from endocytosis defects in larval nephrocytes. Finally, we also show that Past1 null flies harbor more Wolbachia overall and in late egg chambers. Our results identify interactions between Wolbachia and a host protein involved in endocytosis and point to yet another important host cell process impinged upon by Wolbachia's WalE1 effector.

Protein Sorting Prediction

Many computational methods are available for predicting protein sorting in bacteria. When comparing them, it is important to know that they can be grouped into three fundamentally different approaches: signal-based, global property-based, and homology-based prediction. In this chapter, the strengths and drawbacks of each of these approaches are described through many examples of methods that predict secretion, integration into membranes, or subcellular locations in general. The aim of this chapter is to provide a user-level introduction to the field with a minimum of computational theory.

Features and algorithms: facilitating investigation of secreted effectors in Gram-negative bacteria

Gram-negative bacteria deliver effector proteins through type III, IV, or VI secretion systems (T3SSs, T4SSs, and T6SSs) into host cells, causing infections and diseases. In general, effector proteins for each of these distinct secretion systems lack homology and are difficult to identify. Sequence analysis has disclosed many common features, helping us to understand the evolution, function, and secretion mechanisms of the effectors. In combination with various algorithms, the known common features have facilitated accurate prediction of new effectors. Ensemblers or integrated pipelines achieve a better prediction of performance, which combines multiple computational models or modules with multidimensional features. Natural language processing (NLP) models also show the merits, which could enable discovery of novel features and, in turn, facilitate more precise effector prediction, extending our knowledge about each secretion mechanism.

Membrane-dependent actin polymerization mediated by the Legionella pneumophila effector protein MavH

L. pneumophila propagates in eukaryotic cells within a specialized niche, the Legionella-containing vacuole (LCV). The infection process is controlled by over 330 effector proteins delivered through the type IV secretion system. In this study, we report that the Legionella MavH effector localizes to endosomes and remodels host actin cytoskeleton in a phosphatidylinositol 3-phosphate (PI(3)P) dependent manner when ectopically expressed. We show that MavH recruits host actin capping protein (CP) and actin to the endosome via its CP-interacting (CPI) motif and WH2-like actin-binding domain, respectively. In vitro assays revealed that MavH stimulates actin assembly on PI(3)P-containing liposomes causing their tubulation. In addition, the recruitment of CP by MavH negatively regulates F-actin density at the membrane. We further show that, in L. pneumophila-infected cells, MavH appears around the LCV at the very early stage of infection and facilitates bacterium entry into the host. Together, our results reveal a novel mechanism of membrane tubulation induced by membrane-dependent actin polymerization catalyzed by MavH that contributes to the early stage of L. pneumophila infection by regulating host actin dynamics.

Identification and Preliminary Characterization of Novel Type III Secreted Effector Proteins in Chlamydia trachomatis

Chlamydia trachomatis is an obligate intracellular pathogen that replicates in a host-derived vacuole termed the inclusion. Central to pathogenesis is a type III secretion system that translocates effector proteins into the host cell, which are predicted to play major roles in host cell invasion, nutrient acquisition, and immune evasion. However, until recently, the genetic intractability of C. trachomatis hindered identification and characterization of these important virulence factors. Here, we sought to expand the repertoire of identified effector proteins and confirm they are secreted during C. trachomatis infection. Utilizing bioinformatics, we identified 18 candidate substrates that had not been previously assessed for secretion, of which we show four to be secreted, using Yersinia pseudotuberculosis as a surrogate host. Using adenylate cyclase (CyaA), BlaM, and glycogen synthase kinase (GSK) secretion assays, we identified nine novel substrates that were secreted in at least one assay. Interestingly, only three of the substrates, shown to be translocated by C. trachomatis, were similarly secreted by Y. pseudotuberculosis. Using large-scale screens to determine subcellular localization and identify effectors that perturb crucial host cell processes, we identified one novel substrate, CT392, that is toxic when heterologously expressed in Saccharomyces cerevisiae. Toxicity required both the N- and C-terminal regions of the protein. Additionally, we show that these newly described substrates traffic to distinct host cell compartments, including vesicles and the cytoplasm. Collectively, our study expands the known repertoire of C. trachomatis secreted factors and highlights the importance of testing for secretion in the native host using multiple secretion assays when possible.

Peptidoglycan deacetylation controls type IV secretion and the intracellular survival of the bacterial pathogen Legionella pneumophila

Peptidoglycan is a critical component of the bacteria cell envelope. Remodeling of the peptidoglycan is required for numerous essential cellular processes and has been linked to bacterial pathogenesis. Peptidoglycan deacetylases that remove the acetyl group of the N-acetylglucosamine (NAG) subunit protect bacterial pathogens from immune recognition and digestive enzymes secreted at the site of infection. However, the full extent of this modification on bacterial physiology and pathogenesis is not known. Here, we identify a polysaccharide deacetylase of the intracellular bacterial pathogen Legionella pneumophila and define a two-tiered role for this enzyme in Legionella pathogenesis. First, NAG deacetylation is important for the proper localization and function of the Type IVb secretion system, linking peptidoglycan editing to the modulation of host cellular processes through the action of secreted virulence factors. As a consequence, the Legionella vacuole mis-traffics along the endocytic pathway to the lysosome, preventing the formation of a replication permissive compartment. Second, within the lysosome, the inability to deacetylate the peptidoglycan renders the bacteria more sensitive to lysozyme-mediated degradation, resulting in increased bacterial death. Thus, the ability to deacetylate NAG is important for bacteria to persist within host cells and in turn, Legionella virulence. Collectively, these results expand the function of peptidoglycan deacetylases in bacteria, linking peptidoglycan editing, Type IV secretion, and the intracellular fate of a bacterial pathogen.

Complete genome sequence of an Israeli isolate of Xanthomonas hortorum pv. pelargonii strain 305 and novel type III effectors identified in Xanthomonas

Xanthomonas hortorum pv. pelargonii is the causative agent of bacterial blight in geranium ornamental plants, the most threatening bacterial disease of this plant worldwide. Xanthomonas fragariae is the causative agent of angular leaf spot in strawberries, where it poses a significant threat to the strawberry industry. Both pathogens rely on the type III secretion system and the translocation of effector proteins into the plant cells for their pathogenicity. Effectidor is a freely available web server we have previously developed for the prediction of type III effectors in bacterial genomes. Following a complete genome sequencing and assembly of an Israeli isolate of Xanthomonas hortorum pv. pelargonii - strain 305, we used Effectidor to predict effector encoding genes both in this newly sequenced genome, and in X. fragariae strain Fap21, and validated its predictions experimentally. Four and two genes in X. hortorum and X. fragariae, respectively, contained an active translocation signal that allowed the translocation of the reporter AvrBs2 that induced the hypersensitive response in pepper leaves, and are thus considered validated novel effectors. These newly validated effectors are XopBB, XopBC, XopBD, XopBE, XopBF, and XopBG.

Eat or Be Eaten: Strategies Used by Legionella to Acquire Host-Derived Nutrients and Evade Lysosomal Degradation

To replicate within host cells, bacterial pathogens must acquire host-derived nutrients while avoiding degradative antimicrobial pathways. Fundamental insights into bacterial pathogenicity have been revealed by bacteria of the genus Legionella, which naturally parasitize free-living protozoa by establishing a membrane-bound replicative niche termed the Legionella-containing vacuole (LCV). Biogenesis of the LCV and intracellular replication rely on rapid evasion of the endocytic pathway and acquisition of host-derived nutrients, much of which is mediated by bacterial effector proteins translocated into host cells by a Dot/Icm type IV secretion system. Billions of years of co-evolution with eukaryotic hosts and broad host tropism have resulted in expansion of the Legionella genome to accommodate a massive repertoire of effector proteins that promote LCV biogenesis, safeguard the LCV from endolysosomal maturation, and mediate the acquisition of host nutrients. This minireview is focused on the mechanisms by which an ancient intracellular pathogen leverages effector proteins and hijacks host cell biology to obtain essential host-derived nutrients and prevent lysosomal degradation.

Rapid adaptations of Legionella pneumophila to the human host

Legionella pneumophila are host-adapted bacteria that infect and reproduce primarily in amoeboid protists. Using similar infection mechanisms, they infect human macrophages, and cause Legionnaires' disease, an atypical pneumonia, and the milder Pontiac fever. We hypothesized that, despite the similarities in infection mechanisms, the hosts are different enough that there exist high-selective value mutations that would dramatically increase the fitness of Legionella inside the human host. By comparing a large number of isolates from independent infections, we identified two genes, mutated in three unrelated patients, despite the short duration of the incubation period (2-14 days). One is a gene coding for an outer membrane protein (OMP) belonging to the OmpP1/FadL family. The other is a gene coding for an EAL-domain-containing protein involved in cyclic-di-GMP regulation, which in turn modulates flagellar activity. The clinical strain, carrying the mutated EAL-domain-containing homologue, grows faster in macrophages than the wild-type strain, and thus appears to be better adapted to the human host. As human-to-human transmission is very rare, fixation of these mutations into the population and spread into the environment is unlikely. Therefore, parallel evolution - here mutations in the same genes observed in independent human infections - could point to adaptations to the accidental human host. These results suggest that despite the ability of L. pneumophila to infect, replicate in and exit from macrophages, its human-specific adaptations are unlikely to be fixed in the population.

The Wolbachia WalE1 effector alters Drosophila endocytosis

The most common intracellular bacterial infection is Wolbachia pipientis, a microbe that manipulates host reproduction and is used in control of insect vectors. Phenotypes induced by Wolbachia have been studied for decades and range from sperm-egg incompatibility to male killing. How Wolbachia alters host biology is less well understood. Previously, we characterized the first Wolbachia effector - WalE1, which encodes a synuclein domain at the N terminus. Purified WalE1 sediments with and bundles actin and when heterologously expressed in flies, increases Wolbachia titer in the developing oocyte. In this work, we first identify the native expression WalE1 by Wolbachia infecting both fly cells and whole animals. WalE1 appears as aggregates, separate from Wolbachia cells. We next show that WalE1 co-immunoprecipitates with the host protein Past1 and that WalE1 manipulates host endocytosis. Yeast expressing WalE1 show deficiency in uptake of FM4-64 dye, and flies harboring mutations in Past1 or overexpressing WalE1 are sensitive to AgNO3, a hallmark of endocytosis defects. Finally, we also show that Past1 null flies harbor more Wolbachia overall and in late egg chambers. Our results identify interactions between a Wolbachia secreted effector and a host protein and point to yet another important host cell process impinged upon by Wolbachia.

A Versatile Nanoluciferase Reporter Reveals Structural Properties Associated with a Highly Efficient, N-Terminal Legionella pneumophila Type IV Secretion Translocation Signal

Many Gram-negative pathogens rely on type IV secretion systems (T4SS) for infection. One limitation has been the lack of ideal reporters to identify T4SS translocated effectors and study T4SS function. Most reporter systems make use of fusions to reporter proteins, in particular, β-lactamase (TEM) and calmodulin-dependent adenylate cyclase (CYA), that allow detection of translocated enzymatic activity inside host cells. However, both systems require costly reagents and use complex, multistep procedures for loading host cells with substrate (TEM) or for analysis (CYA). Therefore, we have developed and characterized a novel reporter system using nanoluciferase (NLuc) fusions to address these limitations. Serendipitously, we discovered that Nluc itself is efficiently translocated by Legionella pneumophila T4SS in an IcmSW chaperone-dependent manner via an N-terminal translocation signal. Extensive mutagenesis in the NLuc N terminus suggested the importance of an α-helical domain spanning D5 to V9, as mutations predicted to disrupt this structure, with one exception, were translocation defective. Notably, NLuc was capable of translocating several proteins examined when fused to the N or C terminus, while maintaining robust luciferase activity. In particular, it delivered the split GFP11 fragment into J774 macrophages transfected with GFPopt, thereby resulting in in vivo assembly of superfolder green fluorescent protein (GFP). This provided a bifunctional assay in which translocation could be assayed by fluorescence microplate, confocal microscopy, and/or luciferase assays. We further identified an optimal NLuc substrate which allowed a robust, inexpensive, one-step, high-throughput screening assay to identify T4SS translocation substrates and inhibitors. Taken together, these results indicate that NLuc provides both new insight into and also tools for studying T4SS biology. IMPORTANCE Type IV secretion systems (T4SS) are used by Gram-negative pathogens to coopt host cell function. However, the translocation signals recognized by T4SS are not fully explained by primary amino acid sequence, suggesting yet-to-be-defined contributions of secondary and tertiary structure. Here, we unexpectedly identified nanoluciferase (NLuc) as an efficient IcmSW-dependent translocated T4SS substrate, and we provide extensive mutagenesis data suggesting that the first N-terminal, alpha-helix domain is a critical translocation recognition motif. Notably, most existing reporter systems for studying translocated proteins make use of fusions to reporters to permit detection of translocated enzymatic activity inside the host cell. However, existing systems require extremely costly substrates, complex technical procedures to isolate eukaryotic cytoplasm for analysis, and/or are insensitive. Importantly, we found that NLuc provides a powerful, cost-effective new tool to address these limitations and facilitate high-throughput exploration of secretion system biology.

Intrabacterial Regulation of a Cytotoxic Effector by Its Cognate Metaeffector Promotes Legionella pneumophila Virulence

Legionella pneumophila is a natural pathogen of unicellular protozoa that can opportunistically infect macrophages and cause Legionnaires' Disease. Intracellular replication is driven by hundreds of bacterial effector proteins that are translocated into infected host cells by a Dot/Icm type IV secretion system. L. pneumophila effectors are temporally regulated in part by a unique family of translocated regulatory effectors, termed metaeffectors, which bind and modulate the function of a cognate effector in host cells. Regulation of the cytotoxic effector SidI by its cognate metaeffector, MesI, is critical for L. pneumophila virulence in natural and opportunistic hosts. MesI binds and negatively regulates SidI activity in vitro, but how impaired regulation of SidI impairs L. pneumophila intracellular replication is unclear. Using a chromosomally encoded inducible expression system, we found that SidI was toxic to L. pneumophila when uncoupled from MesI. SidI enzymatic activity was required for intrabacterial toxicity since L. pneumophila growth was unaffected by induced expression of a catalytically inactive sidI allele. We also found that MesI translocation into host cells was dispensable for intracellular replication and that MesI-deficient bacteria were rapidly degraded within host cells. These data suggest that MesI promotes L. pneumophila intracellular replication by regulating SidI within the bacterium and reveal a unique role for intrabacterial effector regulation by a translocated metaeffector in L. pneumophila virulence. IMPORTANCE Legionella pneumophila replicates within phagocytic host cells using hundreds of effector protein virulence factors, which canonically subvert the function of host proteins and pathways. L. pneumophila encodes a unique family of translocated effectors called metaeffectors, which bind and regulate the function of a cognate effector in host cells. The metaeffector MesI promotes L. pneumophila virulence by regulating the cytotoxic effector SidI; however, the MesI regulatory mechanism is poorly understood. We discovered a unique intrabacterial role for MesI in L. pneumophila virulence. When uncoupled from MesI, SidI was toxic to L. pneumophila in vitro and triggered robust bacterial degradation in host cells. Furthermore, translocation of MesI was dispensable for intracellular replication, demonstrating that intrabacterial regulation of SidI contributes to L. pneumophila virulence. These data show a novel and important role for translocated effector activity within the bacterium, which challenges the dogma that L. pneumophila effectors function exclusively within host cells.

Membrane-dependent actin polymerization mediated by the Legionella pneumophila effector protein MavH

L. pneumophila propagates in eukaryotic cells within a specialized niche, the Legionella -containing vacuole (LCV). The infection process is controlled by over 330 effector proteins delivered through the type IV secretion system. In this study, we report that the Legionella MavH effector harbors a lipid-binding domain that specifically recognizes PI(3)P (phosphatidylinositol 3-phosphate) and localizes to endosomes when ectopically expressed. We show that MavH recruits host actin capping proteins (CP) and actin to the endosome via its CP interacting (CPI) motif and WH2-like actin-binding domain, respectively. In vitro assays revealed that MavH stimulates robust actin polymerization only in the presence of PI(3)P-containing liposomes and the recruitment of CP by MavH negatively regulates F-actin density at the membrane. Furthermore, in L. pneumophila -infected cells, MavH can be detected around the LCV at the very early stage of infection. Together, our results reveal a novel mechanism of membrane-dependent actin polymerization catalyzed by MavH that may play a role at the early stage of L. pneumophila infection by regulating host actin dynamics.

Recruitment of heterologous substrates by bacterial secretion systems for transkingdom translocation

Bacterial secretion systems mediate the selective exchange of macromolecules between bacteria and their environment, playing a pivotal role in processes such as horizontal gene transfer or virulence. Among the different families of secretion systems, Type III, IV and VI (T3SS, T4SS and T6SS) share the ability to inject their substrates into human cells, opening up the possibility of using them as customized injectors. For this to happen, it is necessary to understand how substrates are recruited and to be able to engineer secretion signals, so that the transmembrane machineries can recognize and translocate the desired substrates in place of their own. Other factors, such as recruiting proteins, chaperones, and the degree of unfolding required to cross through the secretion channel, may also affect transport. Advances in the knowledge of the secretion mechanism have allowed heterologous substrate engineering to accomplish translocation by T3SS, and to a lesser extent, T4SS and T6SS into human cells. In the case of T4SS, transport of nucleoprotein complexes adds a bonus to its biotechnological potential. Here, we review the current knowledge on substrate recognition by these secretion systems, the many examples of heterologous substrate translocation by engineering of secretion signals, and the current and future biotechnological and biomedical applications derived from this approach.

Analysis of the Type 4 Effectome across the Genus Rickettsia

Rickettsia are obligate intracellular bacteria primarily carried by arthropod hosts. The genus Rickettsia contains several vertebrate pathogens vectored by hematophagous arthropods. Despite the potential for disease, our understanding of Rickettsias are limited by the difficulties associated with growing and manipulating obligate intracellular bacteria. To aid with this, our lab conducted an analysis of eight genomes and three plasmids from across the genus Rickettsia. Using OPT4e, a learning algorithm-based program designed to identify effector proteins secreted by the type 4 secretion system, we generated a putative effectome for the genus. We then consolidated effectors into homolog sets to identify effectors unique to Rickettsia with different life strategies or evolutionary histories. We also compared predicted effectors to non-effectors for differences in G+C content and gene splitting. Based on this analysis, we predicted 1571 effectors across the genus, resulting in 604 homolog sets. Each species had unique homolog sets, while 42 were present in all eight species analyzed. Effectors were flagged in association with pathogenic, tick and flea-borne Rickettsia. Predicted effectors also varied in G+C content and frequency of gene splitting as compared to non-effectors. Species effector repertoires show signs of expansion, degradation, and horizontal acquisition associated with lifestyle and lineage.

Natural language processing approach to model the secretion signal of type III effectors

Type III effectors are proteins injected by Gram-negative bacteria into eukaryotic hosts. In many plant and animal pathogens, these effectors manipulate host cellular processes to the benefit of the bacteria. Type III effectors are secreted by a type III secretion system that must "classify" each bacterial protein into one of two categories, either the protein should be translocated or not. It was previously shown that type III effectors have a secretion signal within their N-terminus, however, despite numerous efforts, the exact biochemical identity of this secretion signal is generally unknown. Computational characterization of the secretion signal is important for the identification of novel effectors and for better understanding the molecular translocation mechanism. In this work we developed novel machine-learning algorithms for characterizing the secretion signal in both plant and animal pathogens. Specifically, we represented each protein as a vector in high-dimensional space using Facebook's protein language model. Classification algorithms were next used to separate effectors from non-effector proteins. We subsequently curated a benchmark dataset of hundreds of effectors and thousands of non-effector proteins. We showed that on this curated dataset, our novel approach yielded substantially better classification accuracy compared to previously developed methodologies. We have also tested the hypothesis that plant and animal pathogen effectors are characterized by different secretion signals. Finally, we integrated the novel approach in Effectidor, a web-server for predicting type III effector proteins, leading to a more accurate classification of effectors from non-effectors.

Tailored approach to study Legionella infection using a lattice light sheet microscope (LLSM)

Legionella is a genus of ubiquitous environmental pathogens found in freshwater systems, moist soil, and composted materials. More than four decades of Legionella research has provided important insights into Legionella pathogenesis. Although standard commercial microscopes have led to significant advances in understanding Legionella pathogenesis, great potential exists in the deployment of more advanced imaging techniques to provide additional insights. The lattice light sheet microscope (LLSM) is a recently developed microscope for 4D live cell imaging with high resolution and minimum photo-damage. We built a LLSM with an improved version for the optical layout with two path-stretching mirror sets and a novel reconfigurable galvanometer scanner (RGS) module to improve the reproducibility and reliability of the alignment and maintenance of the LLSM. We commissioned this LLSM to study Legionella pneumophila infection with a tailored workflow designed over instrumentation, experiments, and data processing methods. Our results indicate that Legionella pneumophila infection is correlated with a series of morphological signatures such as smoothness, migration pattern and polarity both statistically and dynamically. Our work demonstrates the benefits of using LLSM for studying long-term questions in bacterial infection. Our free-for-use modifications and workflow designs on the use of LLSM system contributes to the adoption and promotion of the state-of-the-art LLSM technology for both academic and commercial applications.

The Legionella pneumophila Dot/Icm type IV secretion system and its effectors

To prevail in the interaction with eukaryotic hosts, many bacterial pathogens use protein secretion systems to release virulence factors at the host–pathogen interface and/or deliver them directly into host cells. An outstanding example of the complexity and sophistication of secretion systems and the diversity of their protein substrates, effectors, is the Defective in organelle trafficking/Intracellular multiplication (Dot/Icm) Type IVB secretion system (T4BSS) of Legionella pneumophila and related species. Legionella species are facultative intracellular pathogens of environmental protozoa and opportunistic human respiratory pathogens. The Dot/Icm T4BSS translocates an exceptionally large number of effectors, more than 300 per L. pneumophila strain, and is essential for evasion of phagolysosomal degradation and exploitation of protozoa and human macrophages as replicative niches. Recent technological advancements in the imaging of large protein complexes have provided new insight into the architecture of the T4BSS and allowed us to propose models for the transport mechanism. At the same time, significant progress has been made in assigning functions to about a third of L. pneumophila effectors, discovering unprecedented new enzymatic activities and concepts of host subversion. In this review, we describe the current knowledge of the workings of the Dot/Icm T4BSS machinery and provide an overview of the activities and functions of the to-date characterized effectors in the interaction of L. pneumophila with host cells.

Legionella pneumophila temporally regulates the activity of ADP/ATP translocases by reversible ADP-ribosylation

The mitochondrion is an important signaling hub that governs diverse cellular functions, including metabolism, energy production, and immunity. Among the hundreds of effectors translocated into host cells by the Dot/Icm system of Legionella pneumophila, several are targeted to mitochondria but the function of most of them remains elusive. Our recent study found that the effector Ceg3 inhibits the activity of ADP/ATP translocases (ANTs) by ADP-ribosylation (ADPR). Here, we show that the effect of Ceg3 is antagonized by Larg1, an effector encoded by lpg0081, a gene that is situated next to ceg3. Larg1 functions to reverse Ceg3-mediated ADPR of ANTs by cleaving the N-glycosidic bond between the ADPR moiety and the modified arginine residues in ANTs, leading to restoration of their activity in ADP/ATP exchange. Structural analysis of Larg1 and its complex with ADPR reveals that this ADPR glycohydrolase harbors a unique macrodomain that catalyzes the removal of ADPR modification on ANTs. Our results also demonstrate that together with Ceg3, Larg1 imposes temporal regulation of the activity of ANTs by reversible ADPR during L. pneumophila infection.

Legionella pneumophila regulates host cell motility by targeting Phldb2 with a 14-3-3ζ-dependent protease effector

The cytoskeleton network of eukaryotic cells is essential for diverse cellular processes, including vesicle trafficking, cell motility, and immunity, thus is a common target for bacterial virulence factors. A number of effectors from the bacterial pathogen Legionella pneumophila have been shown to modulate the function of host actin cytoskeleton to construct the Legionella-containing vacuole (LCV) permissive for its intracellular replication. In this study, we found that the Dot/Icm effector Lem8 (Lpg1290) is a protease whose activity is catalyzed by a Cys-His-Asp motif known to be associated with diverse biochemical activities. Intriguingly, we found that Lem8 interacts with the host regulatory protein 14-3-3ζ, which activates its protease activity. Furthermore, Lem8 undergoes self-cleavage in a process that requires 14-3-3ζ. We identified the Pleckstrin homology-like domain-containing protein Phldb2 involved in cytoskeleton organization as a target of Lem8 and demonstrated that Lem8 plays a role in the inhibition of host cell migration by attacking Phldb2.

The evolution and role of eukaryotic-like domains in environmental intracellular bacteria: the battle with a eukaryotic cell

Intracellular pathogens that are able to thrive in different environments, such as Legionella spp. which preferentially live in protozoa in aquatic environments or environmental Chlamydiae which replicate either within protozoa or a range of animals, possess a plethora of cellular biology tools to influence their eukaryotic host. The host manipulation tools that evolved in the interaction with protozoa, confer these bacteria the capacity to also infect phylogenetically distinct eukaryotic cells, such as macrophages and thus they can also be human pathogens. To manipulate the host cell, bacteria use protein secretion systems and molecular effectors. Although these molecular effectors are encoded in bacteria, they are expressed and function in a eukaryotic context often mimicking or inhibiting eukaryotic proteins. Indeed, many of these effectors have eukaryotic-like domains. In this review we propose that the main pathways environmental intracellular bacteria need to subvert in order to establish the host eukaryotic cell as a replication niche are chromatin remodelling, ubiquitination signalling, and modulation of protein-protein interactions via tandem repeat domains. We then provide mechanistic insight into how these proteins might have evolved as molecular weapons. Finally, we highlight that in environmental intracellular bacteria the number of eukaryotic-like domains and proteins is considerably higher than in intracellular bacteria specialised to an isolated niche, such as obligate intracellular human pathogens. As mimics of eukaryotic proteins are critical components of host pathogen interactions, this distribution of eukaryotic-like domains suggests that the environment has selected them.

Glycosylating Effectors of Legionella pneumophila: Finding the Sweet Spots for Host Cell Subversion

Work over the past two decades clearly defined a significant role of glycosyltransferase effectors in the infection strategy of the Gram-negative, respiratory pathogen Legionella pneumophila. Identification of the glucosyltransferase effectors Lgt1-3, specifically modifying elongation factor eEF1A, disclosed a novel mechanism of host protein synthesis manipulation by pathogens and illuminated its impact on the physiological state of the target cell, in particular cell cycle progression and immune and stress responses. Recent characterization of SetA as a general O-glucosyltransferase with a wide range of targets including the proteins Rab1 and Snx1, mediators of membrane transport processes, and the discovery of new types of glycosyltransferases such as LtpM and SidI indicate that the vast effector arsenal might still hold more so-far unrecognized family members with new catalytic features and substrates. In this article, we review our current knowledge regarding these fascinating biomolecules and discuss their role in introducing new or overriding endogenous post-translational regulatory mechanisms enabling the subversion of eukaryotic cells by L. pneumophila.

Recent Advancements in Tracking Bacterial Effector Protein Translocation

Bacteria-host interactions are characterized by the delivery of bacterial virulence factors, i.e., effectors, into host cells where they counteract host immunity and exploit host responses allowing bacterial survival and spreading. These effectors are translocated into host cells by means of dedicated secretion systems such as the type 3 secretion system (T3SS). A comprehensive understanding of effector translocation in a spatio-temporal manner is of critical importance to gain insights into an effector’s mode of action. Various approaches have been developed to understand timing and order of effector translocation, quantities of translocated effectors and their subcellular localization upon translocation into host cells. Recently, the existing toolset has been expanded by newly developed state-of-the art methods to monitor bacterial effector translocation and dynamics. In this review, we elaborate on reported methods and discuss recent advances and shortcomings in this area of tracking bacterial effector translocation.

Impact of lockdown and non-pharmaceutical interventions on the epidemiology of Legionnaires' disease

BACKGROUND AND AIM

In order to cope with the requirements of COVID-19 pandemic and prevent overwhelming of the healthcare systems, during 2020 social distancing measures were proposed, and generalized lockdown. Aim of our study is to ascertain whether non-pharmaceutical intervention did have any impact on the epidemiology of Legionnaires' disease (LD), a respiratory infectious disease without interhuman spreading.

METHODS

Official national reports from 4 index countries in European Union (i.e. Germany, France, Italy, and Spain) were retrieved. The study included all cases notified during 2020 COVID-19 outbreak, versus the cases referred during the same period in 2019. Subgroup analyses for hospital-associated and travel-associated LD cases, as well as for lethality estimates were performed.

RESULTS

A sustained drop for incidence rate was confirmed, at EU-level (3.5 per 100,000 vs. 5.3 per 100,000) as well as in the national estimates. The decrease was particularly evident in Italy (RR 0.880, 95%CI 0.839 to 0.905), despite a transient surge in notification rates during the month of June, 2020. Subgroup analyses demonstrated a fall in travel-associated cases (-66.8% at EU level), while hospital-associated cases decreased in absolute number when compared to 2019, but where substantially stable in terms when compared to EU estimates. While Case Fatality Ratio increased in comparison with 2019, no significant trend was similarly identified in comparison to EU estimates.  Conclusions. Lockdown measures have impacted on the epidemiology of LD in Europe during 2020, but some heterogeneities were identified both across the assessed countries, and the various subgroup. Even though the absolute number of total cases did substantially decrease in 2020 compared to 2019, the effect of non-pharmaceutical interventions was mostly indirect, through a reduced interaction of individuals with environments at potentially high-risk for human infections (e.g. hospitals, accommodation sites, etc.).

Predicting Type III Effector Proteins Using the Effectidor Web Server

Various Gram-negative bacteria use secretion systems to secrete effector proteins that manipulate host biochemical pathways to their benefit. We and others have previously developed machine-learning algorithms to predict novel effectors. Specifically, given a set of known effectors and a set of known non-effectors, the machine-learning algorithm extracts features that distinguish these two protein groups. In the training phase, the machine learning learns how to best combine the features to separate the two groups. The trained machine learning is then applied to open reading frames (ORFs) with unknown functions, resulting in a score for each ORF, which is its likelihood to be an effector. We developed Effectidor, a web server for predicting type III effectors. In this book chapter, we provide a step-by-step introduction to the application of Effectidor, from selecting input data to analyzing the obtained predictions.

The Legionella genus core effectors display functional conservation among orthologs by themselves or combined with an accessory protein

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The Legionella genus contains nine core effectors.

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Three Legionella pneumophila core effectors are required for intracellular growth.

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The Legionella genus core effectors display functional conservation among orthologs.

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One Legionella core effector requires an accessory protein to perform its function.

The intracellular pathogen Legionella pneumophila, as well as other Legionella species, utilize the Icm/Dot type-IV secretion system to translocate an exceptionally large and diverse repertoire of effectors into their host cells. However, only nine core effectors were found to be present in all analyzed Legionella species. In this study, we investigated the core effectors, and used intracellular growth complementation to determine whether orthologs of core effectors perform the same function in different Legionella species. We found that three out of the nine L. pneumophila core effectors are required for maximal intracellular growth. Examination of orthologous core effectors from four Legionella species spread over the Legionella phylogenetic tree revealed that most of them perform the same function. Nevertheless, some of the orthologs of the core effector LegA3 did not complement the L. pneumophila legA3 deletion mutant for intracellular growth. LegA3 is encoded as part of an operon together with another gene, which we named legA3C, encoding a non-translocated protein. We found that LegA3 and LegA3C physically interact with each other, are both required for maximal intracellular growth, and the LegA3-LegA3C orthologous pairs from all the Legionella species examined fully complement the L. pneumophila legA3 deletion mutant for intracellular growth. Our results indicate that the Legionella core effectors orthologs generally perform the same function and establish that LegA3 requires LegA3C to fulfill its conserved function.

Recent advances in structural studies of the Legionella pneumophila Dot/Icm type IV secretion system

The intracellular bacterial pathogen Legionella pneumophila utilizes the Dot/Icm type IV secretion system to translocate approximately 300 effector proteins to establish a replicative niche known as the Legionella‐containing vacuole. The Dot/Icm system is classified as a type IVB secretion system, which is evolutionarily closely related to the I‐type conjugation systems and is distinct from type IVA secretion systems, such as the Agrobacterium VirB/D4 system. Although both type IVA and IVB systems directly transport nucleic acids or proteins into the cytosol of recipient cells, the components and architecture of type IVB systems are much more complex than those of type IVA systems. Taking full advantage of rapidly developing cryo‐electron microscopy techniques, the structural details of the transport apparatus and coupling complexes in the Dot/Icm system have been clarified in the past few years. In this review, we summarize recent progress in the structural studies of the L. pneumophila type IVB secretion system and the insights gained into the mechanisms of substrate recognition and transport.

The Legionella pneumophila Effector RavY Contributes to a Replication-Permissive Vacuolar Environment during Infection

Legionella pneumophila is the causative agent of Legionnaires' disease and is capable of replicating inside phagocytic cells, such as mammalian macrophages. The Dot/Icm type IV secretion system is a L. pneumophila virulence factor that is essential for successful intracellular replication. During infection, L. pneumophila builds a replication-permissive vacuole by recruiting multiple host molecules and hijacking host cellular signaling pathways, a process mediated by the coordinated functions of multiple Dot/Icm effector proteins. RavY is a predicted Dot/Icm effector protein found to be important for optimal L. pneumophila replication inside host cells. Here, we demonstrate that RavY is a Dot/Icm-translocated effector protein that is dispensable for axenic replication of L. pneumophila but critical for optimal intracellular replication of the bacteria. RavY is not required for avoidance of endosomal maturation, and RavY does not contribute to the recruitment of host molecules found on replication-permissive vacuoles, such as ubiquitin, RAB1a, and RTN4. Vacuoles containing L. pneumophila ravY mutants promote intracellular survival but limit replication. The replication defect of the L. pneumophila ravY mutant was complemented when the mutant was in the same vacuole as wild-type L. pneumophila. Thus, RavY is an effector that is essential for promoting intracellular replication of L. pneumophila once the specialized vacuole has been established.

Epidemiology of Legionnaires' Disease in Italy, 2004-2019: A Summary of Available Evidence

Legionnaires’ disease (LD) incidence has been increasing in several European countries since 2011. Currently, Italy is experiencing high notification rates for LD, whose cause still remains scarcely understood. We sought to summarize the available evidence on the epidemiology of LD in Italy (2004–2019), characterizing the risk of LD by region, sex, age group, and settings of the case (i.e., community, healthcare, or travel-associated cases). Environmental factors (e.g., average air temperatures and relative humidity) were also included in a Poisson regression model in order to assess their potential role on the annual incidence of new LD cases. National surveillance data included a total of 23,554 LD cases occurring between 2004 and 2019 (70.4% of them were of male gender, 94.1% were aged 40 years and older), with age-adjusted incidence rates increasing from 1.053 cases per 100,000 in 2004 to 4.559 per 100,000 in 2019. The majority of incident cases came from northern Italy (43.2% from northwestern Italy, 25.6% from northeastern Italy). Of these, 5.9% were healthcare-related, and 21.1% were travel-associated. A case-fatality ratio of 5.2% was calculated for the whole of the assessed timeframe, with a pooled estimate for mortality of 0.122 events per 100,000 population per year. Poisson regression analysis was associated with conflicting results, as any increase in average air temperature resulted in reduced risk for LD cases (Incidence Rate Ratio [IRR] 0.807, 95% Confidence Interval [95% CI] 0.744–0.874), while higher annual income in older individuals was associated with an increased IRR (1.238, 95% CI 1.134–1.351). The relative differences in incidence between Italian regions could not be explained by demographic factors (i.e., age and sex distribution of the population), and also a critical reappraisal of environmental factors failed to substantiate both the varying incidence across the country and the decennial trend we were able to identify.

Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning

The advent of inexpensive and rapid sequencing technologies has allowed bacterial whole-genome sequences to be generated at an unprecedented pace. This wealth of information has revealed an unanticipated degree of strain-to-strain genetic diversity within many bacterial species. Awareness of this genetic heterogeneity has corresponded with a greater appreciation of intraspecies variation in virulence. A number of comparative genomic strategies have been developed to link these genotypic and pathogenic differences with the aim of discovering novel virulence factors. Here, we review recent advances in comparative genomic approaches to identify bacterial virulence determinants, with a focus on genome-wide association studies and machine learning.

The extracellular contractile injection system is enriched in environmental microbes and associates with numerous toxins

The extracellular Contractile Injection System (eCIS) is a toxin-delivery particle that evolved from a bacteriophage tail. Four eCISs have previously been shown to mediate interactions between bacteria and their invertebrate hosts. Here, we identify eCIS loci in 1,249 bacterial and archaeal genomes and reveal an enrichment of these loci in environmental microbes and their apparent absence from mammalian pathogens. We show that 13 eCIS-associated toxin genes from diverse microbes can inhibit the growth of bacteria and/or yeast. We identify immunity genes that protect bacteria from self-intoxication, further supporting an antibacterial role for some eCISs. We also identify previously undescribed eCIS core genes, including a conserved eCIS transcriptional regulator. Finally, we present our data through an extensive eCIS repository, termed eCIStem. Our findings support eCIS as a toxin-delivery system that is widespread among environmental prokaryotes and likely mediates antagonistic interactions with eukaryotes and other prokaryotes.

iT4SE-EP: Accurate Identification of Bacterial Type IV Secreted Effectors by Exploring Evolutionary Features from Two PSI-BLAST Profiles

Many gram-negative bacteria use type IV secretion systems to deliver effector molecules to a wide range of target cells. These substrate proteins, which are called type IV secreted effectors (T4SE), manipulate host cell processes during infection, often resulting in severe diseases or even death of the host. Therefore, identification of putative T4SEs has become a very active research topic in bioinformatics due to its vital roles in understanding host-pathogen interactions. PSI-BLAST profiles have been experimentally validated to provide important and discriminatory evolutionary information for various protein classification tasks. In the present study, an accurate computational predictor termed iT4SE-EP was developed for identifying T4SEs by extracting evolutionary features from the position-specific scoring matrix and the position-specific frequency matrix profiles. First, four types of encoding strategies were designed to transform protein sequences into fixed-length feature vectors based on the two profiles. Then, the feature selection technique based on the random forest algorithm was utilized to reduce redundant or irrelevant features without much loss of information. Finally, the optimal features were input into a support vector machine classifier to carry out the prediction of T4SEs. Our experimental results demonstrated that iT4SE-EP outperformed most of existing methods based on the independent dataset test.

Computational prediction of secreted proteins in gram-negative bacteria

Gram-negative bacteria harness multiple protein secretion systems and secrete a large proportion of the proteome. Proteins can be exported to periplasmic space, integrated into membrane, transported into extracellular milieu, or translocated into cytoplasm of contacting cells. It is important for accurate, genome-wide annotation of the secreted proteins and their secretion pathways. In this review, we systematically classified the secreted proteins according to the types of secretion systems in Gram-negative bacteria, summarized the known features of these proteins, and reviewed the algorithms and tools for their prediction.

Type III secretion system effectors form robust and flexible intracellular virulence networks

Infections with many Gram-negative pathogens, including Escherichia coli, Salmonella, Shigella, and Yersinia, rely on type III secretion system (T3SS) effectors. We hypothesized that while hijacking processes within mammalian cells, the effectors operate as a robust network that can tolerate substantial contractions. This was tested in vivo using the mouse pathogen Citrobacter rodentium (encoding 31 effectors). Sequential gene deletions showed that effector essentiality for infection was context dependent and that the network could tolerate 60% contraction while maintaining pathogenicity. Despite inducing very different colonic cytokine profiles (e.g., interleukin-22, interleukin-17, interferon-γ, or granulocyte-macrophage colony-stimulating factor), different networks induced protective immunity. Using data from >100 distinct mutant combinations, we built and trained a machine learning model able to predict colonization outcomes, which were confirmed experimentally. Furthermore, reproducing the human-restricted enteropathogenic E. coli effector repertoire in C. rodentium was not sufficient for efficient colonization, which implicates effector networks in host adaptation. These results unveil the extreme robustness of both T3SS effector networks and host responses.