Common and specific downstream signaling targets controlled by Tlr2 and Tlr5 innate immune signaling in zebrafish

The Spike protein of SARS-CoV-2 signals via Tlr2 in zebrafish

One of the most studied defense mechanisms against invading pathogens, including viruses, are Toll-like receptors (TLRs). Among them, TLR3, TLR7, TLR8 and TLR9 detect different forms of viral nucleic acids in endosomal compartments, whereas TLR2 and TLR4 recognize viral structural and nonstructural proteins outside the cell. Although many different TLRs have been shown to be involved in SARS-CoV-2 infection and detection of different structural proteins, most studies have been performed in vitro and the results obtained are rather contradictory. In this study, we report using the unique advantages of the zebrafish model for in vivo imaging and gene editing that the S1 domain of the Spike protein from the Wuhan strain (S1WT) induced hyperinflammation in zebrafish larvae via a Tlr2/Myd88 signaling pathway and independently of interleukin-1β production. In addition, S1WT also triggered emergency myelopoiesis, but in this case through a Tlr2/Myd88-independent signaling pathway. These results shed light on the mechanisms involved in the fish host responses to viral proteins.

Transcriptomic and Metabolomic Studies Reveal That Toll-like Receptor 2 Has a Role in Glucose-Related Metabolism in Unchallenged Zebrafish Larvae (Danio rerio)

Toll-like receptors (TLRs) have been implicated in the regulation of various metabolism pathways, in addition to their function in innate immunity. Here, we investigate the metabolic function of TLR2 in a larval zebrafish system. We studied larvae from a tlr2 mutant and the wild type sibling controls in an unchallenged normal developmental condition using transcriptomic and metabolomic analyses methods. RNAseq was used to evaluate transcriptomic differences between the tlr2 mutant and wild-type control zebrafish larvae and found a signature set of 149 genes to be significantly altered in gene expression. The expression level of several genes was confirmed by qPCR analyses. Gene set enrichment analysis (GSEA) revealed differential enrichment of genes between the two genotypes related to valine, leucine, and isoleucine degradation and glycolysis and gluconeogenesis. Using ¹H nuclear magnetic resonance (NMR) metabolomics, we found that glucose and various metabolites related with glucose metabolism were present at higher levels in the tlr2 mutant. Furthermore, we confirmed that the glucose level is higher in tlr2 mutants by using a fluorometric assay. Therefore, we have shown that TLR2, in addition to its function in immunity, has a function in controlling metabolism during vertebrate development. The functions are associated with transcriptional regulation of various enzymes involved in glucose metabolism that could explain the different levels of glucose, lactate, succinate, and malate in larvae of a tlr2 mutant.

Transcriptomic profiling of clobetasol propionate-induced immunosuppression in challenged zebrafish embryos

In the ecotoxicological hazard assessment of chemicals, the detection of immunotoxicity is currently neglected. This is mainly due to the complexity of the immune system and the consequent lack of standardized procedures and markers for the comprehensive assessment of immunotoxic modes of action. In this study, we present a new approach applying transcriptome profiling to an immune challenge with a mixture of pathogen-associated molecular patterns (PAMPs) in zebrafish embryos, analyzing differential gene expression during acute infection with and without prior exposure to the immunosuppressive drug clobetasol propionate (CP). While PAMP injection itself triggered biological processes associated with immune activation, some of these genes were more differentially expressed upon prior exposure to CP than by immune induction alone, whereas others showed weaker or no differential regulation in response to the PAMP stimulus. All of these genes responding differently to PAMP after prior CP exposure showed additivity of PAMP- and CP-induced effects, indicating independent regulatory mechanisms. The transcriptomic profiles suggest that CP impaired innate immune induction by attenuating the response of genes involved in antigen processing, TLR signaling, NF-КB signaling, and complement activation. We propose this approach as a powerful method for detecting gene biomarkers for immunosuppressive modes of action, as it was able to identify alternatively regulated processes and pathways in a sublethal, acute infection zebrafish embryo model. This allowed to define biomarker candidates for immune-mediated effects and to comprehensively characterize immunosuppression. Ultimately, this work contributes to the development of molecular biomarker-based environmental hazard assessment of chemicals in the future.

Modeling Virus-Induced Inflammation in Zebrafish: A Balance Between Infection Control and Excessive Inflammation

The inflammatory response to viral infection in humans is a dynamic process with complex cell interactions that are governed by the immune system and influenced by both host and viral factors. Due to this complexity, the relative contributions of the virus and host factors are best studied in vivo using animal models. In this review, we describe how the zebrafish (Danio rerio) has been used as a powerful model to study host-virus interactions and inflammation by combining robust forward and reverse genetic tools with in vivo imaging of transparent embryos and larvae. The innate immune system has an essential role in the initial inflammatory response to viral infection. Focused studies of the innate immune response to viral infection are possible using the zebrafish model as there is a 4-6 week timeframe during development where they have a functional innate immune system dominated by neutrophils and macrophages. During this timeframe, zebrafish lack a functional adaptive immune system, so it is possible to study the innate immune response in isolation. Sequencing of the zebrafish genome has revealed significant genetic conservation with the human genome, and multiple studies have revealed both functional conservation of genes, including those critical to host cell infection and host cell inflammatory response. In addition to studying several fish viruses, zebrafish infection models have been developed for several human viruses, including influenza A, noroviruses, chikungunya, Zika, dengue, herpes simplex virus type 1, Sindbis, and hepatitis C virus. The development of these diverse viral infection models, coupled with the inherent strengths of the zebrafish model, particularly as it relates to our understanding of macrophage and neutrophil biology, offers opportunities for far more intensive studies aimed at understanding conserved host responses to viral infection. In this context, we review aspects relating to the evolution of innate immunity, including the evolution of viral pattern recognition receptors, interferons and interferon receptors, and non-coding RNAs.

Inflammasomes in Teleosts: Structures and Mechanisms That Induce Pyroptosis during Bacterial Infection

Pattern recognition receptors (PRRs) play a crucial role in inducing inflammatory responses; they recognize pathogen-associated molecular patterns, damage-associated molecular patterns, and environmental factors. Nucleotide-binding oligomerization domain-leucine-rich repeat-containing receptors (NLRs) are part of the PRR family; they form a large multiple-protein complex called the inflammasome in the cytosol. In mammals, the inflammasome consists of an NLR, used as a sensor molecule, apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) as an adaptor protein, and pro-caspase1 (Casp1). Inflammasome activation induces Casp1 activation, promoting the maturation of proinflammatory cytokines, such as interleukin (IL)-1β and IL-18, and the induction of inflammatory cell death called pyroptosis via gasdermin D cleavage in mammals. Inflammasome activation and pyroptosis in mammals play important roles in protecting the host from pathogen infection. Recently, numerous inflammasome-related genes in teleosts have been identified, and their conservation and/or differentiation between their expression in mammals and teleosts have also been elucidated. In this review, we summarize the current knowledge of the molecular structure and machinery of the inflammasomes and the ASC-spec to induce pyroptosis; moreover, we explore the protective role of the inflammasome against pathogenic infection in teleosts.

A Novel Function of TLR2 and MyD88 in the Regulation of Leukocyte Cell Migration Behavior During Wounding in Zebrafish Larvae

Toll-like receptor (TLR) signaling via myeloid differentiation factor 88 protein (MyD88) has been indicated to be involved in the response to wounding. It remains unknown whether the putative role of MyD88 in wounding responses is due to a control of leukocyte cell migration. The aim of this study was to explore in vivo whether TLR2 and MyD88 are involved in modulating neutrophil and macrophage cell migration behavior upon zebrafish larval tail wounding. Live cell imaging of tail-wounded larvae was performed in tlr2 and myd88 mutants and their corresponding wild type siblings. In order to visualize cell migration following tissue damage, we constructed double transgenic lines with fluorescent markers for macrophages and neutrophils in all mutant and sibling zebrafish lines. Three days post fertilization (dpf), tail-wounded larvae were studied using confocal laser scanning microscopy (CLSM) to quantify the number of recruited cells at the wounding area. We found that in both tlr2^-/- and myd88^-/- groups the recruited neutrophil and macrophage numbers are decreased compared to their wild type sibling controls. Through analyses of neutrophil and macrophage migration patterns, we demonstrated that both tlr2 and myd88 control the migration direction of distant neutrophils upon wounding. Furthermore, in both the tlr2 and the myd88 mutants, macrophages migrated more slowly toward the wound edge. Taken together, our findings show that tlr2 and myd88 are involved in responses to tail wounding by regulating the behavior and speed of leukocyte migration in vivo.

Senescence-Associated Secretory Phenotype Suppression Mediated by Small-Sized Mesenchymal Stem Cells Delays Cellular Senescence through TLR2 and TLR5 Signaling

In order to provide a sufficient number of cells for clinical use, mesenchymal stem cells (MSCs) must be cultured for long-term expansion, which inevitably triggers cellular senescence. Although the small size of MSCs is known as a critical determinant of their fate, the main regulators of stem cell senescence and the underlying signaling have not been addressed. Umbilical cord blood-derived MSCs (UCB-MSCs) were obtained using size-isolation methods and then cultured with control or small cells to investigate the major factors that modulate MSC senescence. Cytokine array data suggested that the secretion of interukin-8 (IL-8) or growth-regulated oncogene-alpha (GROa) by senescent cells was markedly inhibited during incubation of small cells along with suppression of cognate receptor (C-X-C motif chemokine receptor2, CXCR2) via blockade of the autocrine/paracrine positive loop. Moreover, signaling via toll-like receptor 2 (TLR2) and TLR5, both pattern recognition receptors, drove cellular senescence of MSCs, but was inhibited in small cells. The activation of TLRs (2 and 5) through ligand treatment induced a senescent phenotype in small cells. Collectively, our data suggest that small cell from UCB-MSCs exhibit delayed cellular senescence by inhibiting the process of TLR signaling-mediated senescence-associated secretory phenotype (SASP) activation.

Intake of acrylamide at the dietary relevant concentration causes splenic toxicity in adult zebrafish

Acrylamide (AA) has recently been recognized as an immediate hazardous chemical compound owing to its various toxicities and unavoidable contamination of certain daily foods prepared at a high temperature. AA in foods is thus a worldwide concern; however, its toxicity at the dietary relevant concentration has yet to be experimentally elucidated. To determine whether dietary AA intake causes adverse health effects, adult zebrafish were fed a diet containing AA at a relevant dose for one month. Although AA-fed zebrafish showed no superficial abnormalities, their spleen was severely swollen. Therefore, their spleen was analyzed histologically and pathologically and the changes in cytokine expression in their spleen were also examined. Based on our findings, the intake of AA-containing food caused splenic damages, including cyst formation, hemorrhage, and inflammation, which were accompanied by immune responses as indicated by the appearance of a melanomacrophage center, activation of macrophages, and upregulation of major inflammatory cytokines in the spleen. Collectively, for the first time, we provided experimental evidence of the splenic toxicity caused by dietary AA intake.

Infection and RNA-seq analysis of a zebrafish tlr2 mutant shows a broad function of this toll-like receptor in transcriptional and metabolic control and defense to Mycobacterium marinum infection

Background

The function of Toll-like receptor 2 (TLR2) in host defense against pathogens, especially Mycobacterium tuberculosis (Mtb) is poorly understood. To investigate the role of TLR2 during mycobacterial infection, we analyzed the response of tlr2 zebrafish mutant larvae to infection with Mycobacterium marinum (Mm), a close relative to Mtb, as a model for tuberculosis. We measured infection phenotypes and transcriptome responses using RNA deep sequencing in mutant and control larvae.

Results

tlr2 mutant embryos at 2 dpf do not show differences in numbers of macrophages and neutrophils compared to control embryos. However, we found substantial changes in gene expression in these mutants, particularly in metabolic pathways, when compared with the heterozygote tlr2^+/− control. At 4 days after Mm infection, the total bacterial burden and the presence of extracellular bacteria were higher in tlr2^−/− larvae than in tlr2^+/−, or tlr2^+/+ larvae, whereas granuloma numbers were reduced, showing a function of Tlr2 in zebrafish host defense. RNAseq analysis of infected tlr2^−/− versus tlr2^+/− shows that the number of up-regulated and down-regulated genes in response to infection was greatly diminished in tlr2 mutants by at least 2 fold and 10 fold, respectively. Analysis of the transcriptome data and qPCR validation shows that Mm infection of tlr2 mutants leads to decreased mRNA levels of genes involved in inflammation and immune responses, including il1b, tnfb, cxcl11aa/ac, fosl1a, and cebpb. Furthermore, RNAseq analyses revealed that the expression of genes for Maf family transcription factors, vitamin D receptors, and Dicps proteins is altered in tlr2 mutants with or without infection. In addition, the data indicate a function of Tlr2 in the control of induction of cytokines and chemokines, such as the CXCR3-CXCL11 signaling axis.

Conclusion

The transcriptome and infection burden analyses show a function of Tlr2 as a protective factor against mycobacteria. Transcriptome analysis revealed tlr2-specific pathways involved in Mm infection, which are related to responses to Mtb infection in human macrophages. Considering its dominant function in control of transcriptional processes that govern defense responses and metabolism, the TLR2 protein can be expected to be also of importance for other infectious diseases and interactions with the microbiome.

Aloe emodin induces hepatotoxicity by activating NF-κB inflammatory pathway and P53 apoptosis pathway in zebrafish

The aim of this study was to investigate the hepatotoxic effect and its underlying mechanism of aloe emodin (AE). AE was docked with the targets of NF-κB inflammatory pathway and P53 apoptosis pathway respectively by using molecular docking technique. To verify the results of molecular docking and further investigate the hepatotoxicity mechanism of AE, the zebrafish Tg (fabp10: EGFP) was used as an animal model in vivo. The pathological sections of zebrafish liver were analyzed to observe the histopathological changes and Sudan black B was used to study whether there were inflammatory reactions in zebrafish liver or not. Then TdT-mediated dUTP Nick-End Labeling (TUNEL) was used to detect the apoptotic signal of zebrafish liver cells, finally the mRNA expression levels as well as the protein expression levels of the targets in NF-κB and P53 pathways in zebrafish were measured by quantitative Real-Time PCR (qRT-PCR) and western blot. Molecular docking results showed that AE could successfully dock with all the targets of NF-κB and P53 pathways, and the docking scores of most of the targets were equal to or higher than that of the corresponding ligands. Pathological sections showed AE could cause zebrafish liver lesions and the result of Sudan black B staining revealed that AE blackened the liver of zebrafish with Sudan black B. Then TUNEL assay showed that a large number of dense apoptotic signals were observed in AE group, mainly distributed in the liver and yolk sac of zebrafish. The results of qRT-PCR and western blot showed that AE increased the mRNA and protein expression levels of pro-inflammatory and pro-apoptotic targets in NF-κB and P53 pathways. AE could activate the NF-κB inflammatory pathway and the P53 apoptosis pathway, and its hepatotoxic mechanism was related to activation of NF-κB-P53 inflammation-apoptosis pathways.

Intestinal microbiome adjusts the innate immune setpoint during colonization through negative regulation of MyD88

Host pathways mediating changes in immune states elicited by intestinal microbial colonization are incompletely characterized. Here we describe alterations of the host immune state induced by colonization of germ-free zebrafish larvae with an intestinal microbial community or single bacterial species. We show that microbiota-induced changes in intestinal leukocyte subsets and whole-body host gene expression are dependent on the innate immune adaptor gene myd88. Similar patterns of gene expression are elicited by colonization with conventional microbiome, as well as mono-colonization with two different zebrafish commensal bacterial strains. By studying loss-of-function myd88 mutants, we find that colonization suppresses Myd88 at the mRNA level. Tlr2 is essential for microbiota-induced effects on myd88 transcription and intestinal immune cell composition.

It remains unclear how microbial sensing during early-life colonization results in immune homeostasis rather than acute inflammation. Here the authors show that zebrafish larvae colonization suppresses intestinal MyD88, accounting for a considerable proportion of microbiota-induced alterations in immune setpoint.

Pituitary adenylate cyclase-activating polypeptide (PACAP-38) plays an inhibitory role against inflammation induced by chemical damage to zebrafish hair cells

Pituitary adenylate cyclase-activating polypeptide (PACAP-38) is a common neuropeptide exerting a wide spectrum of functions in many fields, including immunology. In the present study, 5-day post-fertilization (dpf) zebrafish larvae of three diverse genetic lines [transgenic lines Tg(MPX:GFP) with GFP-labelled neutrophils and Tg(pou4f3:GAP-GFP) with GFP-labelled hair cells and the wild-type Tuebingen] were used to investigate an inhibitory role of PACAP-38 in inflammation associated with damaged hair cells of the lateral line. Individuals of each genetic line were assigned to four groups: (1) control, and those consisting of larvae exposed to (2) 10 µM CuSO4, (3) 10 µM CuSO4+100 nM PACAP-38 and (4) 100 nM PACAP-38, respectively. Forty-minute exposure to CuSO4 solution was applied to evoke necrosis of hair cells and consequent inflammation. The inhibitory role of PACAP-38 was investigated in vivo under a confocal microscope by counting neutrophils migrating towards damaged hair cells in Tg(MPX:GFP) larvae. In CuSO4-treated individuals, the number of neutrophils associated with hair cells was dramatically increased, while PACAP-38 co-treatment resulted in its over 2-fold decrease. However, co-treatment with PACAP-38 did not prevent hair cells from extensive necrosis, which was found in Tg(pou4f3:GAP-GFP) individuals. Real-Time PCR analysis performed in wild-type larvae demonstrated differential expression pattern of stress and inflammation inducible markers. The most significant findings showed that CuSO4 exposure up-regulated the expression of IL-8, IL-1β, IL-6 and ATF3, while after PACAP-38 co-treatment expression levels of these genes were significantly decreased. The presence of transcripts for all PACAP receptors in neutrophils was also revealed. Adcyap1r1a and vipr1b appeared to be predominant forms. The present results suggest that PACAP-38 should be considered as a factor playing an important regulatory role in inflammatory response associated with pathological processes affecting zebrafish hair cells and it cannot be excluded that this interesting property has more universal significance.

Duplicated TLR5 of zebrafish functions as a heterodimeric receptor

Toll-like receptor 5 (TLR5) of mammals, birds, and reptiles detects bacterial flagellin and signals as a homodimeric complex. Structural studies using truncated TLR5b of zebrafish confirm the homodimeric TLR5-flagellin interaction. Here we provide evidence that zebrafish (Danio rerio) TLR5 unexpectedly signals as a heterodimer composed of the duplicated gene products drTLR5b and drTLR5a. Flagellin-induced signaling by the zebrafish TLR5 heterodimer increased in the presence of the TLR trafficking chaperone UNC93B1. Targeted exchange of drTLR5b and drTLR5a regions revealed that TLR5 activation needs a heterodimeric configuration of the receptor ectodomain and cytoplasmic domain, consistent with ligand-induced changes in receptor conformation. Structure-guided substitution of the presumed principal flagellin-binding site in human TLR5 with corresponding zebrafish TLR5 residues abrogated human TLR5 activation, indicating a species-specific TLR5-flagellin interaction. Our findings indicate that the duplicated TLR5 of zebrafish underwent subfunctionalization through concerted coevolution to form a unique heterodimeric flagellin receptor that operates fundamentally differently from TLR5 of other species.

Disruption of Trim9 function abrogates macrophage motility in vivo

The vertebrate immune response comprises multiple molecular and cellular components that interface to provide defense against pathogens. Because of the dynamic complexity of the immune system and its interdependent innate and adaptive functionality, an understanding of the whole-organism response to pathogen exposure remains unresolved. Zebrafish larvae provide a unique model for overcoming this obstacle, because larvae are protected against pathogens while lacking a functional adaptive immune system during the first few weeks of life. Zebrafish larvae were exposed to immune agonists for various lengths of time, and a microarray transcriptome analysis was executed. This strategy identified known immune response genes, as well as genes with unknown immune function, including the E3 ubiquitin ligase tripartite motif-9 (Trim9). Although trim9 expression was originally described as "brain specific," its expression has been reported in stimulated human Mϕs. In this study, we found elevated levels of trim9 transcripts in vivo in zebrafish Mϕs after immune stimulation. Trim9 has been implicated in axonal migration, and we therefore investigated the impact of Trim9 disruption on Mϕ motility and found that Mϕ chemotaxis and cellular architecture are subsequently impaired in vivo. These results demonstrate that Trim9 mediates cellular movement and migration in Mϕs as well as neurons.

Omics and cytokine discovery in fish: Presenting the Yellowtail kingfish (Seriola lalandi) as a case study

A continued programme of research is essential to overcome production bottlenecks in any aquacultured fish species. Since the introduction of genetic and molecular techniques, the quality of immune research undertaken in fish has greatly improved. Thousands of species specific cytokine genes have been discovered, which can be used to conduct more sensitive studies to understand how fish physiology is affected by aquaculture environments or disease. Newly available transcriptomic technologies, make it increasingly easier to study the immunogenetics of farmed species for which little data exists. This paper reviews how the application of transcriptomic procedures such as RNA Sequencing (RNA-Seq) can advance fish research. As a case study, we present some preliminary findings using RNA-Seq to identify cytokine related genes in Seriola lalandi. These will allow in-depth investigations to understand the immune responses of these fish in response to environmental change or disease and help in the development of therapeutic approaches.

Identification, characterization and expression analysis of TLR5 in the mucosal tissues of turbot (Scophthalmus maximus L.) following bacterial challenge

TLRs (Toll-like receptors) are very important pathogen pattern recognition receptors, which control the host immune responses against pathogens through recognition of molecular patterns specific to microorganisms. In this regard, investigation of the turbot TLRs could help to understand the immune responses for pathogen recognition. Here, transcripts of two TLR5 (TLR5a and TLR5b) were captured, and their protein structures were also predicted. Meanwhile, we characterized their expression patterns with emphasis on mucosal barriers following different bacterial infection. The phylogenetic analysis revealed the turbot TLR5 genes showed the closest relationship to Paralichthys olivaceus. These two TLR5 genes were ubiquitously expressed in healthy tissues although expression levels varied among the tested tissues. In addition, the two copies of turbot TLR5 showed different expression patterns after bacterial infections. After Vibrio anguillarum infection, TLR5a was generally up-regulated in intestine and skin while down-regulated in gill, while TLR5b showed a general down-regulation in mucosal tissues. After Streptococcus iniae infection, the TLR5a was down-regulated at 2 h while generally up-regulated after 4 h in mucosal tissues. Interestingly, the TLR5b was up-regulated in intestine while down-regulated in skin and gill after Streptococcus iniae infection. These findings suggested a possible irreplaceable role of TLR5 in the immune responses to the infections of a broad range of pathogens that include Gram-negative and Gram-positive bacteria. Future studies should apply the bacteriological and immune-histochemical techniques to study the main sites on the mucosal tissue for bacteria entry and identify the ligand specificity of the turbot TLRs after challenge.

Pattern recognition receptors in zebrafish provide functional and evolutionary insight into innate immune signaling pathways

Pattern recognition receptors (PRRs) and their signaling pathways have essential roles in recognizing various components of pathogens as well as damaged cells and triggering inflammatory responses that eliminate invading microorganisms and damaged cells. The zebrafish relies heavily on these primary defense mechanisms against pathogens. Here, we review the major PRR signaling pathways in the zebrafish innate immune system and compare these signaling pathways in zebrafish and humans to reveal their evolutionary relationship and better understand their innate immune defense mechanisms.

Transcriptomic Approaches in the Zebrafish Model for Tuberculosis-Insights Into Host- and Pathogen-specific Determinants of the Innate Immune Response

Mycobacterium marinum infection in zebrafish has become a well-established model of tuberculosis. Both embryonic and adult zebrafish infection studies have contributed to our knowledge of the development and function of tuberculous granulomas, which are typical of mycobacterial pathogenesis. In this review we discuss how transcriptome profiling studies have helped to characterize this infection process. We illustrate this using new RNA sequencing (RNA-Seq) data that reveals three main phases in the host response to M. marinum during the early stages of granuloma development in zebrafish embryos and larvae. The early phase shows induction of complement and transcription factors, followed by a relatively minor induction of pro-inflammatory cytokines within hours following phagocytosis of M. marinum. A minimal response is observed in the mid-phase, between 6 hours and 1day post infection, when the tissue dissemination of M. marinum begins. During subsequent larval development the granulomas expand and a late-phase response is apparent, which is characterized by progressively increasing induction of complement, transcription factors, pro-inflammatory cytokines, matrix metalloproteinases, and other defense and inflammation-related gene groups. This late-phase response shares common components with the strong and acute host transcriptome response that has previously been reported for Salmonella typhimurium infection in zebrafish embryos. In contrast, the early/mid-phase response to M. marinum infection, characterized by suppressed pro-inflammatory signaling, is strikingly different from the acute response to S. typhimurium infection. Furthermore, M. marinum infection shows a collective and strongly fluctuating regulation of lipoproteins, while S. typhimurium infection has pronounced effects on amino acid metabolism and glycolysis.

Leptospiral outer membrane protein LipL32 induces inflammation and kidney injury in zebrafish larvae

Leptospirosis is an often overlooked cause of acute kidney injury that can lead to multiple organ failure and even death. The principle protein that conserved in many pathogenic leptospires is the outer membrane protein LipL32. However, the role of LipL32 in the pathogenesis of renal injury in leptospirosis is not entirely clear. Here we studied the effects of LipL32 on the developing kidney in zebrafish larvae. Incubation of zebrafish larvae with Leptospira santarosai serovar Shermani induced acute tubular injury predominantly in the proximal pronephric ducts. Furthermore, microinjection of lipl32 mRNA or recombinant LipL32 protein into zebrafish larvae increased macrophage accumulation and disrupted the basolateral location of NA-K-ATPase in pronephric ducts. These changes led to substantial impairment of the pronephric kidney structure. We further demonstrated that morpholino knockdown of tlr2, but not tlr4, reduced the LipL32-induced leukocyte infiltration and kidney injury. These data demonstrate that LipL32 contributes to the renal pathology in leptospirosis and gives some clues to the potential virulence of LipL32. Our results support the use of zebrafish as a model organism for studying the disease mechanism of leptospiral infection. This model might permit the future exploration of the virulence and molecular pathways of different leptospiral outer membrane proteins.

Fungal Innate Immunity Induced by Bacterial Microbe-Associated Molecular Patterns (MAMPs)

Plants and animals detect bacterial presence through Microbe-Associated Molecular Patterns (MAMPs) which induce an innate immune response. The field of fungal-bacterial interaction at the molecular level is still in its infancy and little is known about MAMPs and their detection by fungi. Exposing Fusarium graminearum to bacterial MAMPs led to increased fungal membrane hyperpolarization, a putative defense response, and a range of transcriptional responses. The fungus reacted with a different transcript profile to each of the three tested MAMPs, although a core set of genes related to energy generation, transport, amino acid production, secondary metabolism, and especially iron uptake were detected for all three. Half of the genes related to iron uptake were predicted MirA type transporters that potentially take up bacterial siderophores. These quick responses can be viewed as a preparation for further interactions with beneficial or pathogenic bacteria, and constitute a fungal innate immune response with similarities to those of plants and animals.

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Several different quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that while the presence of differential isoform usage can lead to inflated false discovery rates in differential expression analyses on simple count matrices and transcript-level abundance estimates improve the performance in simulated data, the difference is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.

Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Various quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of performance and interpretability. We also illustrate that the presence of differential isoform usage can lead to inflated false discovery rates in differential gene expression analyses on simple count matrices but that this can be addressed by incorporating offsets derived from transcript-level abundance estimates. We also show that the problem is relatively minor in several real data sets. Finally, we provide an R package ( tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.