Antigen-specific B cells direct T follicular-like helper cells into lymphoid follicles to mediate Mycobacterium tuberculosis control.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a global cause of death. Granuloma-associated lymphoid tissue (GrALT) correlates with protection during TB, but the mechanisms of protection are not understood. During TB, the transcription factor IRF4 in T cells but not B cells is required for the generation of the TH1 and TH17 subsets of helper T cells and follicular helper T (TFH)-like cellular responses. A population of IRF4+ T cells coexpress the transcription factor BCL6 during Mtb infection, and deletion of Bcl6 (Bcl6fl/fl) in CD4+ T cells (CD4cre) resulted in reduction of TFH-like cells, impaired localization within GrALT and increased Mtb burden. In contrast, the absence of germinal center B cells, MHC class II expression on B cells, antibody-producing plasma cells or interleukin-10-expressing B cells, did not increase Mtb susceptibility. Indeed, antigen-specific B cells enhance cytokine production and strategically localize TFH-like cells within GrALT via interactions between programmed cell death 1 (PD-1) and its ligand PD-L1 and mediate Mtb control in both mice and macaques.

A protective role for type I interferon signaling following infection with Mycobacterium tuberculosis carrying the rifampicin drug resistance-conferring RpoB mutation H445Y.

Interleukin-1 (IL-1) signaling is essential for controlling virulent Mycobacterium tuberculosis (Mtb) infection since antagonism of this pathway leads to exacerbated pathology and increased susceptibility. In contrast, the triggering of type I interferon (IFN) signaling is associated with the progression of tuberculosis (TB) disease and linked with negative regulation of IL-1 signaling. However, mice lacking IL-1 signaling can control Mtb infection if infected with an Mtb strain carrying the rifampin-resistance conferring mutation H445Y in its RNA polymerase ß subunit (rpoB-H445Y Mtb). The mechanisms that govern protection in the absence of IL-1 signaling during rpoB-H445Y Mtb infection are unknown. In this study, we show that in the absence of IL-1 signaling, type I IFN signaling controls rpoB-H445Y Mtb replication, lung pathology, and excessive myeloid cell infiltration. Additionally, type I IFN is produced predominantly by monocytes and recruited macrophages and acts on LysM-expressing cells to drive protection through nitric oxide (NO) production to restrict intracellular rpoB-H445Y Mtb. These findings reveal an unexpected protective role for type I IFN signaling in compensating for deficiencies in IL-1 pathways during rpoB-H445Y Mtb infection.

Nuclear Factor κB Signaling Deficiency in CD11c-Expressing Phagocytes Mediates Early Inflammatory Responses and Enhances Mycobacterium tuberculosis Control.

Early innate immune responses play an important role in determining the protective outcome of Mycobacterium tuberculosis (Mtb) infection. Nuclear factor κB (NF-κB) signaling in immune cells regulates the expression of key downstream effector molecules that mount early antimycobacterial responses. Using conditional knockout mice, we studied the effect of abrogation of NF-κB signaling in different myeloid cell types and its impact on Mtb infection. Our results show that the absence of IKK2-mediated signaling in all myeloid cells resulted in increased susceptibility to Mtb infection. In contrast, the absence of IKK2-mediated signaling in CD11c+ myeloid cells induced early proinflammatory cytokine responses, enhanced the recruitment of myeloid cells, and mediated early resistance to Mtb. Abrogation of IKK2 in MRP8-expressing neutrophils did not affect disease pathology or Mtb control. Thus, we describe an early immunoregulatory role for NF-κB signaling in CD11c-expressing phagocytes and a later protective role for NF-κB in LysM-expressing cells during Mtb infection.

Genomic diversity, pathogenicity and antimicrobial resistance of Escherichia coli isolated from poultry in the southern United States.

Escherichia coli (E. coli) are typically present as commensal bacteria in the gastro-intestinal tract of most animals including poultry species, but some avian pathogenic E. coli (APEC) strains can cause localized and even systematic infections in domestic poultry. Emergence and re-emergence of antimicrobial resistant isolates (AMR) constrain antibiotics usage in poultry production, and development of an effective vaccination program remains one of the primary options in E. coli disease prevention and control for domestic poultry. Thus, understanding genetic and pathogenic diversity of the enzootic E. coli isolates, particularly APEC, in poultry farms is the key to designing an optimal vaccine candidate and to developing an effective vaccination program. This study explored the genomic and pathogenic diversity among E. coli isolates in southern United States poultry. A total of nine isolates were recovered from sick broilers from Mississippi, and one from Georgia, with epidemiological variations among clinical signs, type of housing, and bird age. The genomes of these isolates were sequenced by using both Illumina short-reads and Oxford Nanopore long-reads, and our comparative analyses suggested data from both platforms were highly consistent. The 16 s rRNA based phylogenetic analyses showed that the 10 bacteria strains are genetically closer to each other than those in the public database. However, whole genome analyses showed that these 10 isolates encoded a diverse set of reported virulence and AMR genes, belonging to at least nine O:H serotypes, and are genetically clustered with at least five different groups of E. coli isolates reported by other states in the United States. Despite the small sample size, this study suggested that there was a large extent of genomic and serological diversity among E. coli isolates in southern United States poultry. A large-scale comprehensive study is needed to understand the overall genomic diversity and the associated virulence, and such a study will be important to develop a broadly protective E. coli vaccine.

Global dissemination of influenza A virus is driven by wild bird migration through arctic and subarctic zones.

Influenza A viruses (IAV) circulate endemically among many wild aquatic bird populations that seasonally migrate between wintering grounds in southern latitudes to breeding ranges along the perimeter of the circumpolar arctic. Arctic and subarctic zones are hypothesized to serve as ecologic drivers of the intercontinental movement and reassortment of IAVs due to high densities of disparate populations of long distance migratory and native bird species present during breeding seasons. Iceland is a staging ground that connects the East Atlantic and North Atlantic American flyways, providing a unique study system for characterizing viral flow between eastern and western hemispheres. Using Bayesian phylodynamic analyses, we sought to evaluate the viral connectivity of Iceland to proximal regions and how inter-species transmission and reassortment dynamics in this region influence the geographic spread of low and highly pathogenic IAVs. Findings demonstrate that IAV movement in the arctic and subarctic reflects wild bird migration around the perimeter of the circumpolar north, favouring short-distance flights between proximal regions rather than long distance flights over the polar interior. Iceland connects virus movement between mainland Europe and North America, consistent with the westward migration of wild birds from mainland Europe to Northeastern Canada and Greenland. Though virus diffusion rates were similar among avian taxonomic groups in Iceland, gulls play an outsized role as sinks of IAVs from other avian hosts prior to onward migration. These data identify patterns of virus movement in northern latitudes and inform future surveillance strategies related to seasonal and emergent IAVs with potential public health concern.

Response to Hypoxia and the Ensuing Dysregulation of Inflammation Impacts Mycobacterium tuberculosis Pathogenicity.

Rationale: Different Mycobacterium tuberculosis (Mtb) strains exhibit variable degrees of virulence in humans and animal models. Differing stress response strategies used by different strains of Mtb could influence virulence. Objectives: We compared the virulence of two strains of Mtb with use in animal model research: CDC1551 and Erdman. Methods: Rhesus macaques, which develop human-like tuberculosis attributes and pathology, were infected with a high dose of either strain via aerosol, and virulence was compared by bacterial burden and pathology. Measurements and Main Results: Infection with Erdman resulted in significantly shorter times to euthanasia and higher bacterial burdens and greater systemic inflammation and lung pathology relative to those infected with CDC1551. Macaques infected with Erdman also exhibited significantly higher early inflammatory myeloid cell influx to the lung, greater macrophage and T cell activity, and higher expression of lung remodeling (extracellular matrix) genes, consistent with greater pathology. Expression of NOTCH4 (neurogenic locus notch homolog 4) signaling, which is induced in response to hypoxia and promotes undifferentiated cellular state, was also higher in Erdman-infected lungs. The granulomas generated by Erdman, and not CDC1551, infection appeared to have larger regions of necrosis, which is strongly associated with hypoxia. To better understand the mechanisms of differential hypoxia induction by these strains, we subjected both to hypoxia in vitro. Erdman induced higher concentrations of DosR regulon relative to CDC1551. The DosR regulon is the global regulator of response to hypoxia in Mtb and critical for its persistence in granulomas. Conclusions: Our results show that the response to hypoxia is a critical mediator of virulence determination in Mtb, with potential impacts on bacillary persistence, reactivation, and efficiency of therapeutics.

Lung type 3 innate lymphoid cells respond early following Mycobacterium tuberculosis infection.

Tuberculosis is the leading cause of death due to an infectious disease worldwide. Innate lymphoid type 3 cells (ILC3s) mediate early protection during Mycobacterium tuberculosis (Mtb) infection. However, the early signaling mechanisms that govern ILC3 activation or recruitment within the lung during Mtb infection are unclear. scRNA-seq analysis of Mtb-infected mouse lung innate lymphoid cells (ILCs) has revealed the presence of different clusters of ILC populations, suggesting heterogeneity. Using mouse models, we show that during Mtb infection, interleukin-1 receptor (IL-1R) signaling on epithelial cells drives ILC3 expansion and regulates ILC3 accumulation in the lung. Furthermore, our data revealed that C-X-C motif chemokine receptor 5 (CXCR5) signaling plays a crucial role in ILC3 recruitment from periphery during Mtb infection. Our study thus establishes the early responses that drive ILC3 accumulation during Mtb infection and points to ILC3s as a potential vaccine target. IMPORTANCE: Tuberculosis is a leading cause of death due to a single infectious agent accounting for 1.6 million deaths each year. In our study, we determined the role of type 3 innate lymphoid cells in early immune events necessary for achieving protection during Mtb infection. Our study reveals distinct clusters of ILC2, ILC3, and ILC3/ILC1-like cells in Mtb infection. Moreover, our study reveal that IL-1R signaling on lung type 2 epithelial cells plays a key role in lung ILC3 accumulation during Mtb infection. CXCR5 on ILC3s is involved in ILC3 homing from periphery during Mtb infection. Thus, our study provides novel insights into the early immune mechanisms governed by innate lymphoid cells that can be targeted for potential vaccine-induced protection.

A protocol to analyze single-cell RNA-seq data from Mycobacterium tuberculosis-infected mice lung.

Processing and analyzing single-cell RNA-seq (scRNA-seq) from lung cells are challenging due to the complexity of cell subtypes and biological variations within sample groups. Here, we present a protocol for performing an in-depth assessment on lung lymphocyte populations derived from healthy and Mycobacterium tuberculosis-infected mice. We describe steps for downloading processed scRNA-seq data, integrating samples across different conditions, and performing cluster analysis. We then detail procedures for identifying lymphoid cell subtypes, differential analysis, and pathway enrichment analysis. For complete details on the use and execution of this protocol, please refer to Akter et al. (2022).1.

Positive impacts of COVID-19 Lock down in Bangladesh: An online investigation.

Background: This research focuses on the positive impacts of the COVID-19 lockdown on society and the environment, despite acknowledging the widespread negative effects of the pandemic and lockdown measures. The research was aimed at pinpointing and evaluating the beneficial results stemming from these measures. Method: Data for the study was collected through an online survey distributed via Google forms to adults over the age of 18 across the country. A total of 1230 participants completed the survey, mostly from rural areas (61.7%), providing valuable insights for analysis. The questionnaire encompassed personal, family, and cohesive social data, along with information on the environment and biodiversity. The study utilized structural equation modeling (SEM) and confirmatory factor analysis (CFA) to analyze the data and examine correlations between variables. Results: The findings indicated that the COVID-19 lockdown had positive implications for individuals and society, leading to increased health consciousness, improved family relationships, and constructive social attitudes. Moreover, restrictions on access to natural tourist destinations and parks during the lockdown contributed to positive changes in biodiversity. These results highlight the importance of adopting appropriate measures during pandemics to foster personal and social well-being, as well as the preservation of natural environments and biodiversity. Conclusion: This study emphasizes the need for further research to promote sustainable living in similar situations. By understanding the data appropriately, individuals can play a constructive role in future pandemics, leading to positive outcomes for both society and the environment.

Mycobacterium tuberculosis infection drives a type I IFN signature in lung lymphocytes.

Mycobacterium tuberculosis (Mtb) infects 25% of the world's population and causes tuberculosis (TB), which is a leading cause of death globally. A clear understanding of the dynamics of immune response at the cellular level is crucial to design better strategies to control TB. We use the single-cell RNA sequencing approach on lung lymphocytes derived from healthy and Mtb-infected mice. Our results show the enrichment of the type I IFN signature among the lymphoid cell clusters, as well as heat shock responses in natural killer (NK) cells from Mtb-infected mice lungs. We identify Ly6A as a lymphoid cell activation marker and validate its upregulation in activated lymphoid cells following infection. The cross-analysis of the type I IFN signature in human TB-infected peripheral blood samples further validates our results. These findings contribute toward understanding and characterizing the transcriptional parameters at a single-cell depth in a highly relevant and reproducible mouse model of TB.

GenomeForest: An Ensemble Machine Learning Classifier for Endometriosis.

Endometriosis is a complex and high impact disease affecting 176 million women worldwide with diagnostic latency between 4 to 11 years due to lack of a definitive clinical symptom or a minimally invasive diagnostic method. In this study, we developed a new ensemble machine learning classifier based on chromosomal partitioning, named GenomeForest and applied it in classifying the endometriosis vs. the control patients using 38 RNA-seq and 80 enrichment-based DNA-methylation (MBD-seq) datasets, and computed performance assessment with six different experiments. The ensemble machine learning models provided an avenue for identifying several candidate biomarker genes with a very high F1 score; a near perfect F1 score (0.968) for the transcriptomics dataset and a very high F1 score (0.918) for the methylomics dataset. We hope in the future a less invasive biopsy can be used to diagnose endometriosis using the findings from such ensemble machine learning classifiers, as demonstrated in this study.

Machine Learning Classifiers for Endometriosis Using Transcriptomics and Methylomics Data.

Endometriosis is a complex and common gynecological disorder yet a poorly understood disease affecting about 176 million women worldwide and causing significant impact on their quality of life and economic burden. Neither a definitive clinical symptom nor a minimally invasive diagnostic method is available, thus leading to an average of 4 to 11 years of diagnostic latency. Discovery of relevant biological patterns from microarray expression or next generation sequencing (NGS) data has been advanced over the last several decades by applying various machine learning tools. We performed machine learning analysis using 38 RNA-seq and 80 enrichment-based DNA methylation (MBD-seq) datasets. We experimented how well various supervised machine learning methods such as decision tree, partial least squares discriminant analysis (PLSDA), support vector machine, and random forest perform in classifying endometriosis from the control samples trained on both transcriptomics and methylomics data. The assessment was done from two different perspectives for improving classification performances: a) implication of three different normalization techniques and b) implication of differential analysis using the generalized linear model (GLM). Several candidate biomarker genes were identified by multiple machine learning experiments including NOTCH3, SNAPC2, B4GALNT1, SMAP2, DDB2, GTF3C5, and PTOV1 from the transcriptomics data analysis and TRPM6, RASSF2, TNIP2, RP3-522J7.6, FGD3, and MFSD14B from the methylomics data analysis. We concluded that an appropriate machine learning diagnostic pipeline for endometriosis should use TMM normalization for transcriptomics data, and quantile or voom normalization for methylomics data, GLM for feature space reduction and classification performance maximization.

Transcriptomic effects of metformin in skeletal muscle arteries of obese insulin-resistant rats.

We examined the effects of metformin, a commonly used antidiabetic drug, on gene expression in multiple arteries. Specifically, transcriptional profiles of feed arteries and second branch order arterioles in the soleus, gastrocnemius, and diaphragm muscles as well as aortic endothelial scrapes were examined from obese insulin-resistant Otsuka Long-Evans Tokushima Fatty rats treated with ( n = 9) or without ( n = 10) metformin from 20 to 32 weeks of age. Metformin-treated rats exhibited a reduction in body weight, adiposity, and HbA1c ( P < 0.05). The greatest number of differentially expressed genes (FDR < 15%) between those treated with and without metformin was found in the red gastrocnemius 2a arterioles (93 genes), followed by the diaphragm 2a arterioles (62 genes), and soleus 2a arterioles (15 genes). We also found that two genes were differentially expressed in aortic endothelial cells (LETMD1 and HMGCS2, both downregulated), one gene in the gastrocnemius feed artery (BLNK, downregulated), and no genes in the soleus and diaphragm feed arteries and white gastrocnemius 2a arterioles. No single gene was altered by metformin across all vessels examined. This study provides evidence that metformin treatment produces distinct gene expression effects throughout the arterial tree in a rat model of obesity and insulin resistance. Genes whose expression was modulated with metformin do not appear to have a clear connection with its known mechanisms of action. These findings support the notion that vascular gene regulation in response to oral pharmacological therapy, such as metformin, is vessel specific. Impact statement This study provides evidence that metformin treatment produces artery-specific gene expression effects. The genes whose expression was modulated with metformin do not appear to have a clear connection with its known mechanisms of action.

Exercise-induced differential changes in gene expression among arterioles of skeletal muscles of obese rats.

Using next-generation, transcriptome-wide RNA sequencing (RNA-Seq) technology we assessed the effects of exercise training on transcriptional profiles in skeletal muscle arterioles isolated from the soleus and gastrocnemius muscles of Otsuka Long Evans Tokushima Fatty (OLETF) rats that underwent an endurance exercise training program (EX; n = 13), interval sprint training program (SPRINT; n = 14), or remained sedentary (Sed; n = 12). We hypothesized that the greatest effects of exercise would be in the gastrocnemius arterioles. Results show that EX caused the largest number of changes in gene expression in the soleus and white gastrocnemius 2a arterioles with little to no changes in the feed arteries. In contrast, SPRINT caused substantial changes in gene expression in the feed arteries. IPA canonical pathway analysis revealed 18 pathways with significant changes in gene expression when analyzed across vessels and revealed that EX induces increased expression of the following genes in all arterioles examined: Shc1, desert hedgehog protein (Dhh), adenylate cyclase 4 (Adcy4), G protein binding protein, alpha (Gnat1), and Bcl2l1 and decreased expression of ubiquitin D (Ubd) and cAMP response element modulator (Crem). EX increased expression of endothelin converting enzyme (Ece1), Hsp90b, Fkbp5, and Cdcl4b in four of five arterioles. SPRINT had effects on expression of Crem, Dhh, Bcl2l1, and Ubd that were similar to EX. SPRINT also increased expression of Nfkbia, Hspa5, Tubb 2a and Tubb 2b, and Fkbp5 in all five arterioles and increased expression of Gnat1 in all but the soleus second-order arterioles. Many contractile and/or structural protein genes were increased by SPRINT in the gastrocnemius feed artery, but the same genes exhibited decreased expression in red gastrocnemius arterioles. We conclude that training-induced changes in arteriolar gene expression patterns differ by muscle fiber type composition and along the arteriolar tree.

Exercise training causes differential changes in gene expression in diaphragm arteries and 2A arterioles of obese rats.

We employed next-generation, transcriptome-wide RNA sequencing (RNA-Seq) technology to assess the effects of two different exercise training protocols on transcriptional profiles in diaphragm second-order arterioles (D2a) and in the diaphragm feed artery (DFA) from Otsuka Long Evans Tokushima Fatty (OLETF) rats. Arterioles were isolated from the diaphragm of OLETF rats that underwent an endurance exercise training program (EX; n = 13), interval sprint training program (SPRINT; n = 14), or remained sedentary (Sed; n = 12). Our hypothesis was that exercise training would have similar effects on gene expression in the diaphragm and soleus muscle arterioles because diaphragm blood flow increases during exercise to a similar extent as in soleus. Results reveal that several canonical pathways that were significantly altered by exercise in limb skeletal muscles were not among the pathways significantly changed in the diaphragm arterioles including actin cytoskeleton signaling, role of NFAT in regulation of immune response, protein kinase A signaling, and protein ubiquitination pathway. EX training altered the expression of a smaller number of genes than did SPRINT in the DFA but induced a larger number of genes with altered expression in the D2a than did SPRINT. In fact, FDR differential expression analysis (FDR, 10%) indicated that only two genes exhibited altered expression in D2a of SPRINT rats. Very few of the genes that exhibited altered expression in the DFA or D2a were also altered in limb muscle arterioles. Finally, results indicate that the 2a arterioles of soleus muscle (S2a) from endurance-trained animals and the DFA of SPRINT animals exhibited the largest number of genes with altered expression.

Differential susceptibility to colorectal cancer due to naturally occurring gut microbiota.

Recent studies investigating the human microbiome have identified particular bacterial species that correlate with the presence of colorectal cancer. To evaluate the role of qualitatively different but naturally occurring gut microbiota and the relationship with colorectal cancer development, genetically identical embryos from the Polyposis in Rat Colon (Pirc) rat model of colorectal cancer were transferred into recipients of three different genetic backgrounds (F344/NHsd, LEW/SsNHsd, and Crl:SD). Tumor development in the pups was tracked longitudinally via colonoscopy, and end-stage tumor burden was determined. To confirm vertical transmission and identify associations between the gut microbiota and disease phenotype, the fecal microbiota was characterized in recipient dams 24 hours pre-partum, and in Pirc rat offspring prior to and during disease progression. Our data show that the gut microbiota varies between rat strains, with LEW/SsNHsd having a greater relative abundance of the bacteria Prevotella copri. The mature gut microbiota of pups resembled the profile of their dams, indicating that the dam is the primary determinant of the developing microbiota. Both male and female F344-Pirc rats harboring the Lewis microbiota had decreased tumor burden relative to genetically identical rats harboring F344 or SD microbiota. Significant negative correlations were detected between tumor burden and the relative abundance of specific taxa from samples taken at weaning and shortly thereafter, prior to observable adenoma development. Notably, this naturally occurring variation in the gut microbiota is associated with a significant difference in severity of colorectal cancer, and the abundance of certain taxa is associated with decreased tumor burden.