Increased Interferon-Induced Protein With Tetracopeptides (IFITs) Reduces Mycobacterial Growth

Amoebae as training grounds for microbial pathogens

Grazing of amoebae on microorganisms represents one of the oldest predator-prey dynamic relationships in nature. It represents a genetic "melting pot" for an ancient and continuous multi-directional inter- and intra-kingdom horizontal gene transfer between amoebae and its preys, intracellular microbial residents, endosymbionts, and giant viruses, which has shaped the evolution, selection, and adaptation of microbes that evade degradation by predatory amoeba. Unicellular phagocytic amoebae are thought to be the ancient ancestors of macrophages with highly conserved eukaryotic processes. Selection and evolution of microbes within amoeba through their evolution to target highly conserved eukaryotic processes have facilitated the expansion of their host range to mammals, causing various infectious diseases. Legionella and environmental Chlamydia harbor an immense number of eukaryotic-like proteins that are involved in ubiquitin-related processes or are tandem repeats-containing proteins involved in protein-protein and protein-chromatin interactions. Some of these eukaryotic-like proteins exhibit novel domain architecture and novel enzymatic functions absent in mammalian cells, such as ubiquitin ligases, likely acquired from amoebae. Mammalian cells and amoebae may respond similarly to microbial factors that target highly conserved eukaryotic processes, but mammalian cells may undergo an accidental response to amoeba-adapted microbial factors. We discuss specific examples of microbes that have evolved to evade amoeba predation, including the bacterial pathogens- Legionella, Chlamydia, Coxiella, Rickettssia, Francisella, Mycobacteria, Salmonella, Bartonella, Rhodococcus, Pseudomonas, Vibrio, Helicobacter, Campylobacter, and Aliarcobacter. We also discuss the fungi Cryptococcus, and Asperigillus, as well as amoebae mimiviruses/giant viruses. We propose that amoeba-microbe interactions will continue to be a major "training ground" for the evolution, selection, adaptation, and emergence of microbial pathogens equipped with unique pathogenic tools to infect mammalian hosts. However, our progress will continue to be highly dependent on additional genomic, biochemical, and cellular data of unicellular eukaryotes.

Host Cell Death and Modulation of Immune Response against Mycobacterium tuberculosis Infection

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis (TB), a prevalent infectious disease affecting populations worldwide. A classic trait of TB pathology is the formation of granulomas, which wall off the pathogen, via the innate and adaptive immune systems. Some key players involved include tumor necrosis factor-alpha (TNF-α), foamy macrophages, type I interferons (IFNs), and reactive oxygen species, which may also show overlap with cell death pathways. Additionally, host cell death is a primary method for combating and controlling Mtb within the body, a process which is influenced by both host and bacterial factors. These cell death modalities have distinct molecular mechanisms and pathways. Programmed cell death (PCD), encompassing apoptosis and autophagy, typically confers a protective response against Mtb by containing the bacteria within dead macrophages, facilitating their phagocytosis by uninfected or neighboring cells, whereas necrotic cell death benefits the pathogen, leading to the release of bacteria extracellularly. Apoptosis is triggered via intrinsic and extrinsic caspase-dependent pathways as well as caspase-independent pathways. Necrosis is induced via various pathways, including necroptosis, pyroptosis, and ferroptosis. Given the pivotal role of host cell death pathways in host defense against Mtb, therapeutic agents targeting cell death signaling have been investigated for TB treatment. This review provides an overview of the diverse mechanisms underlying Mtb-induced host cell death, examining their implications for host immunity. Furthermore, it discusses the potential of targeting host cell death pathways as therapeutic and preventive strategies against Mtb infection.

Identification of hub genes and establishment of a diagnostic model in tuberculosis infection

Tuberculosis (TB) poses significant challenges due to its high transmissibility within populations and intrinsic resistance to treatment, rendering it a formidable respiratory disease with a substantial susceptibility burden. This study was designed to identify new potential therapeutic targets for TB and establish a diagnostic model. mRNA expression data for TB were from GEO database, followed by conducting differential expression analysis. The top 50 genes with differential expression were subjected to GO and KEGG enrichment analyses. To establish a PPI network, the STRING database was utilized, and hub genes were identified utilizing five algorithms (EPC, MCC, MNC, Radiality, and Stress) within the cytoHubba plugin of Cytoscape software. Furthermore, a hub gene co-expression network was constructed using the GeneMANIA database. Consistency clustering was performed on hub genes, and ssGSEA was utilized to analyze the extent of immune infiltration in different subgroups. LASSO analysis was employed to construct a diagnostic model, and ROC curves were used for validation. Through the analysis of GEO data, a total of 159 genes were identified as differentially expressed. Further, GO and KEGG enrichment analyses revealed that these genes were mainly enriched in viral defense, symbiotic defense, and innate immune response-related pathways. Hub genes, including DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15, were identified using cytoHubba analysis of the PPI network. The GeneMANIA analysis unmasked that the co-expression rate of hub genes was 81.55%, and the physical interaction rate was 12.27%. Consistency clustering divided TB patients into two subgroups, and ssGSEA revealed different degrees of immune infiltration in different subgroups. LASSO analysis identified IFIT1, IFIT2, IFIT3, IFIH1, RSAD2, OAS1, OAS2, and STAT1 as eight immune-related key genes, and a diagnostic model was constructed. The ROC curve demonstrated that the model exhibited excellent diagnostic performance. DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15 were hub genes in TB, and the diagnostic model based on eight immune-related key genes exhibited good diagnostic performance.

Differential transcriptome response of blood brain barrier spheroids to neuroinvasive Neisseria and Borrelia

Background

The blood-brain barrier (BBB), a highly regulated interface between the blood and the brain, prevents blood-borne substances and pathogens from entering the CNS. Nevertheless, pathogens like Neisseria meningitidis and Borrelia bavariensis can breach the BBB and infect the brain parenchyma. The self-assembling BBB-spheroids can simulate the cross talk occurring between the cells of the barrier and neuroinvasive pathogens.

Methods

BBB spheroids were generated by co-culturing human brain microvascular endothelial cells (hBMECs), pericytes and astrocytes. The BBB attributes of spheroids were confirmed by mapping the localization of cells, observing permeability of angiopep2 and non-permeability of dextran. Fluorescent Neisseria, Borrelia or E. coli (non-neuroinvasive) were incubated with spheroids to observe the adherence, invasion and spheroid integrity. Transcriptome analysis with NGS was employed to investigate the response of BBB cells to infections.

Results

hBMECs were localized throughout the spheroids, whereas pericytes and astrocytes were concentrated around the core. Within 1 hr of exposure, Neisseria and Borrelia adhered to spheroids, and their microcolonization increased from 5 to 24 hrs. Integrity of spheroids was compromised by both Neisseria and Borrelia, but not by E. coli infection. Transcriptome analysis revealed a significant change in the expression of 781 genes (467 up and 314 down regulated) in spheroids infected with Neisseria, while Borrelia altered the expression of 621 genes (225 up and 396 down regulated). The differentially expressed genes could be clustered into various biological pathways like cell adhesion, extracellular matrix related, metallothionines, members of TGF beta, WNT signaling, and immune response. Among the differentially expressed genes, 455 (48%) genes were inversely expressed during Neisseria and Borrelia infection.

Conclusion

The self-assembling spheroids were used to perceive the BBB response to neuroinvasive pathogens - Neisseria and Borrelia. Compromised integrity of spheroids during Neisseria and Borrelia infection as opposed to its intactness and non-adherence of E. coli (non-neuroinvasive) denotes the pathogen dependent fate of BBB. Genes categorized into various biological functions indicated weakened barrier properties of BBB and heightened innate immune response. Inverse expression of 48% genes commonly identified during Neisseria and Borrelia infection exemplifies unique response of BBB to varying neuropathogens.

Immunomodulatory effects of inactivated Ligilactobacillus salivarius CECT 9609 on respiratory epithelial cells

The microbiota in humans and animals play crucial roles in defense against pathogens and offer a promising natural source for immunomodulatory products. However, the development of physiologically relevant model systems and protocols for testing such products remains challenging. In this study, we present an experimental condition where various natural products derived from the registered lactic acid bacteria Ligilactobacillus salivarius CECT 9609, known for their immunomodulatory activity, were tested. These products included live and inactivated bacteria, as well as fermentation products at different concentrations and culture times. Using our established model system, we observed no morphological changes in the airway epithelium upon exposure to Pasteurella multocida, a common respiratory pathogen. However, early molecular changes associated with the innate immune response were detected through transcript analysis. By employing diverse methodologies ranging from microscopy to next-generation sequencing (NGS), we characterized the interaction of these natural products with the airway epithelium and their potential beneficial effects in the presence of P. multocida infection. In particular, our discovery highlights that among all Ligilactobacillus salivarius CECT 9609 products tested, only inactivated cells preserve the conformation and morphology of respiratory epithelial cells, while also reversing or altering the natural immune responses triggered by Pasteurella multocida. These findings lay the groundwork for further exploration into the protective role of these bacteria and their derivatives.