Defensin-like peptides in wheat analyzed by whole-transcriptome sequencing: a focus on structural diversity and role in induced resistance

Antimicrobial peptides (AMPs) are the main components of the plant innate immune system. Defensins represent the most important AMP family involved in defense and non-defense functions. In this work, global RNA sequencing and de novo transcriptome assembly were performed to explore the diversity of defensin-like (DEFL) genes in the wheat Triticum kiharae and to study their role in induced resistance (IR) mediated by the elicitor metabolites of a non-pathogenic strain FS-94 of Fusarium sambucinum. Using a combination of two pipelines for DEFL mining in transcriptome data sets, as many as 143 DEFL genes were identified in T. kiharae, the vast majority of them represent novel genes. According to the number of cysteine residues and the cysteine motif, wheat DEFLs were classified into ten groups. Classical defensins with a characteristic 8-Cys motif assigned to group 1 DEFLs represent the most abundant group comprising 52 family members. DEFLs with a characteristic 4-Cys motif CX{3,5}CX{8,17}CX{4,6}C named group 4 DEFLs previously found only in legumes were discovered in wheat. Within DEFL groups, subgroups of similar sequences originated by duplication events were isolated. Variation among DEFLs within subgroups is due to amino acid substitutions and insertions/deletions of amino acid sequences. To identify IR-related DEFL genes, transcriptional changes in DEFL gene expression during elicitor-mediated IR were monitored. Transcriptional diversity of DEFL genes in wheat seedlings in response to the fungus Fusarium oxysporum, FS-94 elicitors, and the combination of both (elicitors + fungus) was demonstrated, with specific sets of up- and down-regulated DEFL genes. DEFL expression profiling allowed us to gain insight into the mode of action of the elicitors from F. sambucinum. We discovered that the elicitors up-regulated a set of 24 DEFL genes. After challenge inoculation with F. oxysporum, another set of 22 DEFLs showed enhanced expression in IR-displaying seedlings. These DEFLs, in concert with other defense molecules, are suggested to determine enhanced resistance of elicitor-pretreated wheat seedlings. In addition to providing a better understanding of the mode of action of the elicitors from FS-94 in controlling diseases, up-regulated IR-specific DEFL genes represent novel candidates for genetic transformation of plants and development of pathogen-resistant crops

Multi-level analysis of the gut-brain axis shows autism spectrum disorder-associated molecular and microbial profiles

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD

CRISPR-Cas Systems in Gut Microbiome of Children with Autism Spectrum Disorders

The human gut microbiome is associated with various diseases, including autism spectrum disorders (ASD). Variations of the taxonomical composition in the gut microbiome of children with ASD have been observed repeatedly. However, features and parameters of the microbiome CRISPR-Cas systems in ASD have not been investigated yet. Here, we demonstrate such an analysis in order to describe the overall changes in the microbiome CRISPR-Cas systems during ASD as well as to reveal their potential to be used in diagnostics and therapy. For the systems identification, we used a combination of the publicly available tools suited for completed genomes with subsequent filtrations. In the considered data, the microbiomes of children with ASD contained fewer arrays per Gb of assembly than the control group, but the arrays included more spacers on average. CRISPR arrays from the microbiomes of children with ASD differed from the control group neither in the fractions of spacers with protospacers from known genomes, nor in the sets of known bacteriophages providing protospacers. Almost all bacterial protospacers of the gut microbiome systems for both children with ASD and the healthy ones were located in prophage islands, leaving no room for the systems to participate in the interspecies competition

Alterations of the Composition and Neurometabolic Profile of Human Gut Microbiota in Major Depressive Disorder

Major depressive disorder (MDD) is among the most prevalent mental disorders worldwide. Factors causing the pathogenesis of MDD include gut microbiota (GM), which interacts with the host through the gut–brain axis. In previous studies of GM in MDD patients, 16S rRNA sequencing was used, which provided information about composition but not about function. In our study, we analyzed whole metagenome sequencing data to assess changes in both the composition and functional profile of GM. We looked at the GM of 36 MDD patients, compared with that of 38 healthy volunteers. Comparative taxonomic analysis showed decreased abundances of Faecalibacterium prausnitzii, Roseburia hominis, and Roseburia intestinalis, and elevated abundances of Escherichia coli and Ruthenibacterium lactatiformans in the GM of MDD patients. We observed decreased levels of bacterial genes encoding key enzymes involved in the production of arginine, asparagine, glutamate, glutamine, melatonin, acetic, butyric and conjugated linoleic acids, and spermidine in MDD patients. These genes produced signature pairs with Faecalibacterium prausntizii and correlated with decreased levels of this species in the GM of MDD patients. These results show the potential impact of the identified biomarker bacteria and their metabolites on the pathogenesis of MDD, and should be confirmed in future metabolomic studies

Non-Specific Lipid Transfer Proteins in Triticum kiharae Dorof. et Migush.: Identification, Characterization and Expression Profiling in Response to Pathogens and Resistance Inducers

Non-specific lipid-transfer proteins (nsLTPs) represent a family of plant antimicrobial peptides (AMPs) implicated in diverse physiological processes. However, their role in induced resistance (IR) triggered by non-pathogenic fungal strains and their metabolites is poorly understood. In this work, using RNA-seq data and our AMP search pipeline, we analyzed the repertoire of nsLTP genes in the wheat Triticum kiharae and studied their expression in response to Fusarium oxysporum infection and treatment with the intracellular metabolites of Fusarium sambucinum FS-94. A total of 243 putative nsLTPs were identified, which were classified into five structural types and characterized. Expression analysis showed that 121 TkLTPs including sets of paralogs with identical mature peptides displayed specific expression patters in response to different treatments pointing to their diverse roles in resistance development. We speculate that upregulated nsLTP genes are involved in protection due to their antimicrobial activity or signaling functions. Furthermore, we discovered that in IR-displaying plants, a vast majority of nsLTP genes were downregulated, suggesting their role as negative regulators of immune mechanisms activated by the FS-94 elicitors. The results obtained add to our knowledge of the role of nsLTPs in IR and provide candidate molecules for genetic engineering of crops to enhance disease resistance

Bacterial Metabolites of Human Gut Microbiota Correlating with Depression

Depression is a global threat to mental health that affects around 264 million people worldwide. Despite the considerable evolution in our understanding of the pathophysiology of depression, no reliable biomarkers that have contributed to objective diagnoses and clinical therapy currently exist. The discovery of the microbiota-gut-brain axis induced scientists to study the role of gut microbiota (GM) in the pathogenesis of depression. Over the last decade, many of studies were conducted in this field. The productions of metabolites and compounds with neuroactive and immunomodulatory properties among mechanisms such as the mediating effects of the GM on the brain, have been identified. This comprehensive review was focused on low molecular weight compounds implicated in depression as potential products of the GM. The other possible mechanisms of GM involvement in depression were presented, as well as changes in the composition of the microbiota of patients with depression. In conclusion, the therapeutic potential of functional foods and psychobiotics in relieving depression were considered. The described biomarkers associated with GM could potentially enhance the diagnostic criteria for depressive disorders in clinical practice and represent a potential future diagnostic tool based on metagenomic technologies for assessing the development of depressive disorders

Multi-level analysis of the gut-brain axis shows autism spectrum disorder-associated molecular and microbial profiles.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD