An integrated cell atlas of the lung in health and disease.

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1+ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas.

Yersiniomics, a Multi-Omics Interactive Database for Yersinia Species.

The genus Yersinia includes a large variety of nonpathogenic and life-threatening pathogenic bacteria, which cause a broad spectrum of diseases in humans and animals, such as plague, enteritis, Far East scarlet-like fever (FESLF), and enteric redmouth disease. Like most clinically relevant microorganisms, Yersinia spp. are currently subjected to intense multi-omics investigations whose numbers have increased extensively in recent years, generating massive amounts of data useful for diagnostic and therapeutic developments. The lack of a simple and centralized way to exploit these data led us to design Yersiniomics, a web-based platform allowing straightforward analysis of Yersinia omics data. Yersiniomics contains a curated multi-omics database at its core, gathering 200 genomic, 317 transcriptomic, and 62 proteomic data sets for Yersinia species. It integrates genomic, transcriptomic, and proteomic browsers, a genome viewer, and a heatmap viewer to navigate within genomes and experimental conditions. For streamlined access to structural and functional properties, it directly links each gene to GenBank, the Kyoto Encyclopedia of Genes and Genomes (KEGG), UniProt, InterPro, IntAct, and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and each experiment to Gene Expression Omnibus (GEO), the European Nucleotide Archive (ENA), or the Proteomics Identifications Database (PRIDE). Yersiniomics provides a powerful tool for microbiologists to assist with investigations ranging from specific gene studies to systems biology studies. IMPORTANCE The expanding genus Yersinia is composed of multiple nonpathogenic species and a few pathogenic species, including the deadly etiologic agent of plague, Yersinia pestis. In 2 decades, the number of genomic, transcriptomic, and proteomic studies on Yersinia grew massively, delivering a wealth of data. We developed Yersiniomics, an interactive web-based platform, to centralize and analyze omics data sets on Yersinia species. The platform allows user-friendly navigation between genomic data, expression data, and experimental conditions. Yersiniomics will be a valuable tool to microbiologists.

Immunopeptidomics-based design of mRNA vaccine formulations against Listeria monocytogenes.

Listeria monocytogenes is a foodborne intracellular bacterial pathogen leading to human listeriosis. Despite a high mortality rate and increasing antibiotic resistance no clinically approved vaccine against Listeria is available. Attenuated Listeria strains offer protection and are tested as antitumor vaccine vectors, but would benefit from a better knowledge on immunodominant vector antigens. To identify novel antigens, we screen for Listeria peptides presented on the surface of infected human cell lines by mass spectrometry-based immunopeptidomics. In between more than 15,000 human self-peptides, we detect 68 Listeria immunopeptides from 42 different bacterial proteins, including several known antigens. Peptides presented on different cell lines are often derived from the same bacterial surface proteins, classifying these antigens as potential vaccine candidates. Encoding these highly presented antigens in lipid nanoparticle mRNA vaccine formulations results in specific CD8+ T-cell responses and induces protection in vaccination challenge experiments in mice. Our results can serve as a starting point for the development of a clinical mRNA vaccine against Listeria and aid to improve attenuated Listeria vaccines and vectors, demonstrating the power of immunopeptidomics for next-generation bacterial vaccine development.

Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics.

Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.

Bacnet: a user-friendly platform for building multi-omics websites.

SUMMARY: To face up to the exponential growth of heterogeneous datasets of various organisms, we developed a user-friendly platform for building multi-omics websites, which is named Bacnet. This platform helps bioinformaticians to construct four key web interfaces: (i) an interactive genome viewer; (ii) an expression and protein atlas; (iii) an interface for analysis of co-expression network; (iv) an interface for exploring homolog presence. We believe our platform will help the bioinformaticians to construct personalized user interfaces dedicated to biologists studying non-reference organisms. AVAILABILITY AND IMPLEMENTATION: https://github.com/becavin-lab/bacnet; Java; Eclipse RAP; Eclipse RCP.

A Single-Cell Atlas of the Human Healthy Airways.

Rationale: The respiratory tract constitutes an elaborate line of defense that is based on a unique cellular ecosystem.Objectives: We aimed to investigate cell population distributions and transcriptional changes along the airways by using single-cell RNA profiling.Methods: We have explored the cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. A total of 77,969 cells were collected at 35 distinct locations, from the nose to the 12th division of the airway tree.Measurements and Main Results: The resulting atlas is composed of a high percentage of epithelial cells (89.1%) but also immune (6.2%) and stromal (4.7%) cells with distinct cellular proportions in different regions of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (MUC4, PI3, SIX3) and tracheobronchial (SCGB1A1, TFF3) airways. By contrast, cell-type-specific gene expression is stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuroendocrine cells, and brush cells and identifies a related population of NREP-positive cells. We also report the association of KRT13 with dividing cells that are reminiscent of previously described mouse "hillock" cells and with squamous cells expressing SCEL and SPRR1A/B.Conclusions: Robust characterization of a single-cell cohort in healthy airways establishes a valuable resource for future investigations. The precise description of the continuum existing from the nasal epithelium to successive divisions of the airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed.

SARS-CoV-2 Entry Genes Are Most Highly Expressed in Nasal Goblet and Ciliated Cells within Human Airways.

The SARS-CoV-2 coronavirus, the etiologic agent responsible for COVID-19 coronavirus disease, is a global threat. To better understand viral tropism, we assessed the RNA expression of the coronavirus receptor, ACE2, as well as the viral S protein priming protease TMPRSS2 thought to govern viral entry in single-cell RNA-sequencing (scRNA-seq) datasets from healthy individuals generated by the Human Cell Atlas consortium. We found that ACE2, as well as the protease TMPRSS2, are differentially expressed in respiratory and gut epithelial cells. In-depth analysis of epithelial cells in the respiratory tree reveals that nasal epithelial cells, specifically goblet/secretory cells and ciliated cells, display the highest ACE2 expression of all the epithelial cells analyzed. The skewed expression of viral receptors/entry-associated proteins towards the upper airway may be correlated with enhanced transmissivity. Finally, we showed that many of the top genes associated with ACE2 airway epithelial expression are innate immune-associated, antiviral genes, highly enriched in the nasal epithelial cells. This association with immune pathways might have clinical implications for the course of infection and viral pathology, and highlights the specific significance of nasal epithelia in viral infection. Our findings underscore the importance of the availability of the Human Cell Atlas as a reference dataset. In this instance, analysis of the compendium of data points to a particularly relevant role for nasal goblet and ciliated cells as early viral targets and potential reservoirs of SARS-CoV-2 infection. This, in turn, serves as a biological framework for dissecting viral transmission and developing clinical strategies for prevention and therapy.

SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes.

We investigated SARS-CoV-2 potential tropism by surveying expression of viral entry-associated genes in single-cell RNA-sequencing data from multiple tissues from healthy human donors. We co-detected these transcripts in specific respiratory, corneal and intestinal epithelial cells, potentially explaining the high efficiency of SARS-CoV-2 transmission. These genes are co-expressed in nasal epithelial cells with genes involved in innate immunity, highlighting the cells' potential role in initial viral infection, spread and clearance. The study offers a useful resource for further lines of inquiry with valuable clinical samples from COVID-19 patients and we provide our data in a comprehensive, open and user-friendly fashion at www.covid19cellatlas.org.

Impact of the gut microbiota on the m6A epitranscriptome of mouse cecum and liver.

The intestinal microbiota modulates host physiology and gene expression via mechanisms that are not fully understood. Here we examine whether host epitranscriptomic marks are affected by the gut microbiota. We use methylated RNA-immunoprecipitation and sequencing (MeRIP-seq) to identify N6-methyladenosine (m6A) modifications in mRNA of mice carrying conventional, modified, or no microbiota. We find that variations in the gut microbiota correlate with m6A modifications in the cecum, and to a lesser extent in the liver, affecting pathways related to metabolism, inflammation and antimicrobial responses. We analyze expression levels of several known writer and eraser enzymes, and find that the methyltransferase Mettl16 is downregulated in absence of a microbiota, and one of its target mRNAs, encoding S-adenosylmethionine synthase Mat2a, is less methylated. We furthermore show that Akkermansia muciniphila and Lactobacillus plantarum affect specific m6A modifications in mono-associated mice. Our results highlight epitranscriptomic modifications as an additional level of interaction between commensal bacteria and their host.

An RNA-Binding Protein Secreted by a Bacterial Pathogen Modulates RIG-I Signaling.

RNA-binding proteins (RBPs) perform key cellular activities by controlling the function of bound RNAs. The widely held assumption that RBPs are strictly intracellular has been challenged by the discovery of secreted RBPs. However, extracellular RBPs have been described in eukaryotes, while secreted bacterial RBPs have not been reported. Here, we show that the bacterial pathogen Listeria monocytogenes secretes a small RBP that we named Zea. We show that Zea binds a subset of L. monocytogenes RNAs, causing their accumulation in the extracellular medium. Furthermore, during L. monocytogenes infection, Zea binds RIG-I, the non-self-RNA innate immunity sensor, potentiating interferon-ß production. Mouse infection studies reveal that Zea affects L. monocytogenes virulence. Together, our results unveil that bacterial RNAs can be present extracellularly in association with RBPs, acting as "social RNAs" to trigger a host response during infection.

Genome-wide CRISPR-dCas9 screens in E. coli identify essential genes and phage host factors.

High-throughput genetic screens are powerful methods to identify genes linked to a given phenotype. The catalytic null mutant of the Cas9 RNA-guided nuclease (dCas9) can be conveniently used to silence genes of interest in a method also known as CRISPRi. Here, we report a genome-wide CRISPR-dCas9 screen using a starting pool of ~ 92,000 sgRNAs which target random positions in the chromosome of E. coli. To benchmark our method, we first investigate its utility to predict gene essentiality in the genome of E. coli during growth in rich medium. We could identify 79% of the genes previously reported as essential and demonstrate the non-essentiality of some genes annotated as essential. In addition, we took advantage of the intermediate repression levels obtained when targeting the template strand of genes to show that cells are very sensitive to the expression level of a limited set of essential genes. Our data can be visualized on CRISPRbrowser, a custom web interface available at crispr.pasteur.fr. We then apply the screen to discover E. coli genes required by phages λ, T4 and 186 to kill their host, highlighting the involvement of diverse host pathways in the infection process of the three tested phages. We also identify colanic acid capsule synthesis as a shared resistance mechanism to all three phages. Finally, using a plasmid packaging system and a transduction assay, we identify genes required for the formation of functional λ capsids, thus covering the entire phage cycle. This study demonstrates the usefulness and convenience of pooled genome-wide CRISPR-dCas9 screens in bacteria and paves the way for their broader use as a powerful tool in bacterial genomics.

Author Correction: N-terminomics identifies Prli42 as a membrane miniprotein conserved in Firmicutes and critical for stressosome activation in Listeria monocytogenes.

This Article contains a URL for a publically available whole-genome browser ( http://nterm.listeriomics.pasteur.fr ). However, due to technical constraint, this website has been replaced with an alternative ( https://listeriomics.pasteur.fr ).

Unraveling the evolution and coevolution of small regulatory RNAs and coding genes in Listeria.

BACKGROUND: Small regulatory RNAs (sRNAs) are widely found in bacteria and play key roles in many important physiological and adaptation processes. Studying their evolution and screening for events of coevolution with other genomic features is a powerful way to better understand their origin and assess a common functional or adaptive relationship between them. However, evolution and coevolution of sRNAs with coding genes have been sparsely investigated in bacterial pathogens. RESULTS: We designed a robust and generic phylogenomics approach that detects correlated evolution between sRNAs and protein-coding genes using their observed and inferred patterns of presence-absence in a set of annotated genomes. We applied this approach on 79 complete genomes of the Listeria genus and identified fifty-two accessory sRNAs, of which most were present in the Listeria common ancestor and lost during Listeria evolution. We detected significant coevolution between 23 sRNA and 52 coding genes and inferred the Listeria sRNA-coding genes coevolution network. We characterized a main hub of 12 sRNAs that coevolved with genes encoding cell wall proteins and virulence factors. Among them, an sRNA specific to L. monocytogenes species, rli133, coevolved with genes involved either in pathogenicity or in interaction with host cells, possibly acting as a direct negative post-transcriptional regulation. CONCLUSIONS: Our approach allowed the identification of candidate sRNAs potentially involved in pathogenicity and host interaction, consistent with recent findings on known pathogenicity actors. We highlight four sRNAs coevolving with seven internalin genes, some of which being important virulence factors in Listeria.

Listeriomics: an Interactive Web Platform for Systems Biology of Listeria.

As for many model organisms, the amount of Listeria omics data produced has recently increased exponentially. There are now >80 published complete Listeria genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the Listeria phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete Listeria species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis. IMPORTANCE In the last decades, Listeria has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach.

Genome-Wide Transcriptional Start Site Mapping and sRNA Identification in the Pathogen Leptospira interrogans.

Leptospira are emerging zoonotic pathogens transmitted from animals to humans typically through contaminated environmental sources of water and soil. Regulatory pathways of pathogenic Leptospira spp. underlying the adaptive response to different hosts and environmental conditions remains elusive. In this study, we provide the first global Transcriptional Start Site (TSS) map of a Leptospira species. RNA was obtained from the pathogen Leptospira interrogans grown at 30°C (optimal in vitro temperature) and 37°C (host temperature) and selectively enriched for 5' ends of native transcripts. A total of 2865 and 2866 primary TSS (pTSS) were predicted in the genome of L. interrogans at 30 and 37°C, respectively. The majority of the pTSSs were located between 0 and 10 nucleotides from the translational start site, suggesting that leaderless transcripts are a common feature of the leptospiral translational landscape. Comparative differential RNA-sequencing (dRNA-seq) analysis revealed conservation of most pTSS at 30 and 37°C. Promoter prediction algorithms allow the identification of the binding sites of the alternative sigma factor sigma 54. However, other motifs were not identified indicating that Leptospira consensus promoter sequences are inherently different from the Escherichia coli model. RNA sequencing also identified 277 and 226 putative small regulatory RNAs (sRNAs) at 30 and 37°C, respectively, including eight validated sRNAs by Northern blots. These results provide the first global view of TSS and the repertoire of sRNAs in L. interrogans. These data will establish a foundation for future experimental work on gene regulation under various environmental conditions including those in the host.

N-terminomics identifies Prli42 as a membrane miniprotein conserved in Firmicutes and critical for stressosome activation in Listeria monocytogenes.

To adapt to changing environments, bacteria have evolved numerous pathways that activate stress response genes. In Gram-positive bacteria, the stressosome, a cytoplasmic complex, relays external cues and activates the sigma B regulon. The stressosome is structurally well-characterized in Bacillus, but how it senses stress remains elusive. Here, we report a genome-wide N-terminomic approach in Listeria that strikingly led to the discovery of 19 internal translation initiation sites and 6 miniproteins, among which one, Prli42, is conserved in Firmicutes. Prli42 is membrane-anchored and interacts with orthologues of Bacillus stressosome components. We reconstituted the Listeria stressosome in vitro and visualized its supramolecular structure by electron microscopy. Analysis of a series of Prli42 mutants demonstrated that Prli42 is important for sigma B activation, bacterial growth following oxidative stress and for survival in macrophages. Taken together, our N-terminonic approach unveiled Prli42 as a long-sought link between stress and the stressosome.

Evidence of IL-17, IP-10, and IL-10 involvement in multiple-organ dysfunction and IL-17 pathway in acute renal failure associated to Plasmodium falciparum malaria.

BACKGROUND: Plasmodium falciparum malaria in India is characterized by high rates of severe disease, with multiple organ dysfunction (MOD)-mainly associated with acute renal failure (ARF)-and increased mortality. The objective of this study is to identify cytokine signatures differentiating severe malaria patients with MOD, cerebral malaria (CM), and cerebral malaria with MOD (CM-MOD) in India. We have previously shown that two cytokines clusters differentiated CM from mild malaria in Maharashtra. Hence, we also aimed to determine if these cytokines could discriminate malaria subphenotypes in Odisha. METHODS: P. falciparum malaria patients from the SCB Medical College Cuttack in the Odisha state in India were enrolled along with three sets of controls: healthy individuals, patients with sepsis and encephalitis (n = 222). We determined plasma concentrations of pro- and anti-inflammatory cytokines and chemokines for all individuals using a multiplex assay. We then used an ensemble of statistical analytical methods to ascertain whether particular sets of cytokines/chemokines were predictors of severity or signatures of a disease category. RESULTS: Of the 26 cytokines/chemokines tested, 19 increased significantly during malaria and clearly distinguished malaria patients from controls, as well as sepsis and encephalitis patients. High amounts of IL-17, IP-10, and IL-10 predicted MOD, decreased IL-17 and MIP-1α segregated CM-MOD from MOD, and increased IL-12p40 differentiated CM from CM-MOD. Most severe malaria patients with ARF exhibited high levels of IL-17. CONCLUSION: We report distinct differences in cytokine production correlating with malarial disease severity in Odisha and Maharashtra populations in India. We show that CM, CM-MOD and MOD are clearly distinct malaria-associated pathologies. High amounts of IL-17, IP-10, and IL-10 were predictors of MOD; decreased IL-17 and MIP-1α separated CM-MOD from MOD; and increased IL-12p40 differentiated CM from CM-MOD. Data also suggest that the IL-17 pathway may contribute to malaria pathogenesis via different regulatory mechanisms and may represent an interesting target to mitigate the pathological processes in malaria-associated ARF.

Asymptomatic Plasmodium falciparum infection in children is associated with increased auto-antibody production, high IL-10 plasma levels and antibodies to merozoite surface protein 3.

BACKGROUND: Mechanisms of acquired protection to malaria in asymptomatic Plasmodium falciparum carriers are only partially understood. Among them, the role plays by the self-reactive antibodies has not been clarified yet. In this study, the relationship between repertoires of circulating self-reactive and parasite-specific immunoglobulin G (IgG), their correlation with cytokine levels, and their association with protection against malaria was investigated in asymptomatic Plasmodium falciparum-infected Gabonese children. METHODS: The diversity of P. falciparum-specific antibody repertoire was analysed using a protein micro-array immunoassay, the total auto-antibody repertoire by quantitative immunoblotting and circulating cytokine levels were measured by ELISA in endemic controls (EC) and P. falciparum-infected children from Gabon with asymptomatic (AM) or mild malaria (MM). The association of self- and parasite-specific antibody repertoires with circulating cytokines was evaluated using single linkage hierarchical clustering, Kruskal-Wallis tests and Spearman's rank correlation. RESULTS: Children with AM exhibited an IgG response to merozoite surface protein 3 (MSP3) but not to MSP1-19, although their levels of total P. falciparum-specific IgG were similar to those in the MM group. Moreover, the asymptomatic children had increased levels of autoantibodies recognising brain antigens. In addition, a correlation between IL-10 levels and parasite load was found in AM and MM children. These two groups also exhibited significant correlations between plasma levels of IL-10 and IFN-γ with age and with total plasma IgG levels. IL-10 and IFN-γ levels were also associated with auto-antibody responses in AM. CONCLUSIONS: Altogether, these results indicate that a self-reactive polyclonal response associated with increased IgG to MSP3 and high plasma levels of IL-10 and IFN-γ may contribute to protective immune mechanisms triggered in asymptomatic P. falciparum infection in Gabonese children.

Comparison of widely used Listeria monocytogenes strains EGD, 10403S, and EGD-e highlights genomic variations underlying differences in pathogenicity.

For nearly 3 decades, listeriologists and immunologists have used mainly three strains of the same serovar (1/2a) to analyze the virulence of the bacterial pathogen Listeria monocytogenes. The genomes of two of these strains, EGD-e and 10403S, were released in 2001 and 2008, respectively. Here we report the genome sequence of the third reference strain, EGD, and extensive genomic and phenotypic comparisons of the three strains. Strikingly, EGD-e is genetically highly distinct from EGD (29,016 single nucleotide polymorphisms [SNPs]) and 10403S (30,296 SNPs), and is more related to serovar 1/2c than 1/2a strains. We also found that while EGD and 10403S strains are genetically very close (317 SNPs), EGD has a point mutation in the transcriptional regulator PrfA (PrfA*), leading to constitutive expression of several major virulence genes. We generated an EGD-e PrfA* mutant and showed that EGD behaves like this strain in vitro, with slower growth in broth and higher invasiveness in human cells than those of EGD-e and 10403S. In contrast, bacterial counts in blood, liver, and spleen during infection in mice revealed that EGD and 10403S are less virulent than EGD-e, which is itself less virulent than EGD-e PrfA*. Thus, constitutive expression of PrfA-regulated virulence genes does not appear to provide a significant advantage to the EGD strain during infection in vivo, highlighting the fact that in vitro invasion assays are not sufficient for evaluating the pathogenic potential of L. monocytogenes strains. Together, our results pave the way for deciphering unexplained differences or discrepancies in experiments using different L. monocytogenes strains. IMPORTANCE Over the past 3 decades, Listeria has become a model organism for host-pathogen interactions, leading to critical discoveries in a broad range of fields, including bacterial gene regulation, cell biology, and bacterial pathophysiology. Scientists studying Listeria use primarily three pathogenic strains: EGD, EGD-e, and 10403S. Despite many studies on EGD, it is the only one of the three strains whose genome has not been sequenced. Here we report the sequence of its genome and a series of important genomic and phenotypic differences between the three strains, in particular, a critical mutation in EGD's PrfA, the main regulator of Listeria virulence. Our results show that the three strains display differences which may play an important role in the virulence differences observed between the strains. Our findings will be of critical relevance to listeriologists and immunologists who have used or may use Listeria as a tool to study the pathophysiology of listeriosis and immune responses.

The intestinal microbiota interferes with the microRNA response upon oral Listeria infection.

UNLABELLED: The intestinal tract is the largest reservoir of microbes in the human body. The intestinal microbiota is thought to be able to modulate alterations of the gut induced by enteropathogens, thereby maintaining homeostasis. Listeria monocytogenes is the agent of listeriosis, an infection transmitted to humans upon ingestion of contaminated food. Crossing of the intestinal barrier is a critical step of the infection before dissemination into deeper organs. Here, we investigated the role of the intestinal microbiota in the regulation of host protein-coding genes and microRNA (miRNA or miR) expression during Listeria infection. We first established the intestinal miRNA signatures corresponding to the 10 most highly expressed miRNAs in the murine ileum of conventional and germfree mice, noninfected and infected with Listeria. Next, we identified 6 miRNAs whose expression decreased upon Listeria infection in conventional mice. Strikingly, five of these miRNA expression variations (in miR-143, miR-148a, miR-200b, miR-200c, and miR-378) were dependent on the presence of the microbiota. In addition, as is already known, protein-coding genes were highly affected by infection in both conventional and germfree mice. By crossing bioinformatically the predicted targets of the miRNAs to our whole-genome transcriptomic data, we revealed an miRNA-mRNA network that suggested miRNA-mediated global regulation during intestinal infection. Other recent studies have revealed an miRNA response to either bacterial pathogens or commensal bacteria. In contrast, our work provides an unprecedented insight into the impact of the intestinal microbiota on host transcriptional reprogramming during infection by a human pathogen. IMPORTANCE: While the crucial role of miRNAs in regulating the host response to bacterial infection is increasingly recognized, the involvement of the intestinal microbiota in the regulation of miRNA expression has not been explored in detail. Here, we investigated the impact of the intestinal microbiota on the regulation of protein-coding genes and miRNA expression in a host infected by L. monocytogenes, a food-borne pathogen. We show that the microbiota interferes with the microRNA response upon oral Listeria infection and identify several protein-coding target genes whose expression correlates inversely with that of the miRNA. Further investigations of the regulatory networks involving miR-143, miR-148a, miR-200b, miR-200c, and miR-378 will provide new insights into the impact of the intestinal microbiota on the host upon bacterial infection.