Transcriptome-Wide Identification and Expression Analysis of Genes Encoding Defense-Related Peptides of Filipendula ulmaria in Response to Bipolaris sorokiniana Infection.

Peptides play an essential role in plant development and immunity. Filipendula ulmaria, belonging to the Rosaceae family, is a medicinal plant which exhibits valuable pharmacological properties. F. ulmaria extracts in vitro inhibit the growth of a variety of plant and human pathogens. The role of peptides in defense against pathogens in F. ulmaria remains unknown. The objective of this study was to explore the repertoire of antimicrobial (AMPs) and defense-related signaling peptide genes expressed by F. ulmaria in response to infection with Bipolaris sorokiniana using RNA-seq. Transcriptomes of healthy and infected plants at two time points were sequenced on the Illumina HiSeq500 platform and de novo assembled. A total of 84 peptide genes encoding novel putative AMPs and signaling peptides were predicted in F. ulmaria transcriptomes. They belong to known, as well as new, peptide families. Transcriptional profiling in response to infection disclosed complex expression patterns of peptide genes and identified both up- and down-regulated genes in each family. Among the differentially expressed genes, the vast majority were down-regulated, suggesting suppression of the immune response by the fungus. The expression of 13 peptide genes was up-regulated, indicating their possible involvement in triggering defense response. After functional studies, the encoded peptides can be used in the development of novel biofungicides and resistance inducers.

Unveiling the Connection between Microbiota and Depressive Disorder through Machine Learning.

In the last few years, investigation of the gut-brain axis and the connection between the gut microbiota and the human nervous system and mental health has become one of the most popular topics. Correlations between the taxonomic and functional changes in gut microbiota and major depressive disorder have been shown in several studies. Machine learning provides a promising approach to analyze large-scale metagenomic data and identify biomarkers associated with depression. In this work, machine learning algorithms, such as random forest, elastic net, and You Only Look Once (YOLO), were utilized to detect significant features in microbiome samples and classify individuals based on their disorder status. The analysis was conducted on metagenomic data obtained during the study of gut microbiota of healthy people and patients with major depressive disorder. The YOLO method showed the greatest effectiveness in the analysis of the metagenomic samples and confirmed the experimental results on the critical importance of a reduction in the amount of Faecalibacterium prausnitzii for the manifestation of depression. These findings could contribute to a better understanding of the role of the gut microbiota in major depressive disorder and potentially lead the way for novel diagnostic and therapeutic strategies.

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.

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.

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.

Molecular Insights into the Role of Cysteine-Rich Peptides in Induced Resistance to Fusarium oxysporum Infection in Tomato Based on Transcriptome Profiling.

Cysteine-rich peptides (CRPs) play an important role in plant physiology. However, their role in resistance induced by biogenic elicitors remains poorly understood. Using whole-genome transcriptome sequencing and our CRP search algorithm, we analyzed the repertoire of CRPs in tomato Solanum lycopersicum L. in response to Fusarium oxysporum infection and elicitors from F. sambucinum. We revealed 106 putative CRP transcripts belonging to different families of antimicrobial peptides (AMPs), signaling peptides (RALFs), and peptides with non-defense functions (Major pollen allergen of Olea europaea (Ole e 1 and 6), Maternally Expressed Gene (MEG), Epidermal Patterning Factor (EPF)), as well as pathogenesis-related proteins of families 1 and 4 (PR-1 and 4). We discovered a novel type of 10-Cys-containing hevein-like AMPs named SlHev1, which was up-regulated both by infection and elicitors. Transcript profiling showed that F. oxysporum infection and F. sambucinum elicitors changed the expression levels of different overlapping sets of CRP genes, suggesting the diversification of functions in CRP families. We showed that non-specific lipid transfer proteins (nsLTPs) and snakins mostly contribute to the response of tomato plants to the infection and the elicitors. The involvement of CRPs with non-defense function in stress reactions was also demonstrated. The results obtained shed light on the mode of action of F. sambucinum elicitors and the role of CRP families in the immune response in tomato.

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.

The bacterial neurometabolic signature of the gut microbiota of young children with autism spectrum disorders.

Introduction. The human gut microbiota is currently seen as an important factor that can promote autism spectrum disorder (ASD) development in children.Aim. This study aimed to detect differences in the taxonomic composition and content of bacterial genes encoding key enzymes involved in the metabolism of neuroactive biomarker compounds in the metagenomes of gut microbiota of children with ASD and neurotypical children.Methodology. A whole metagenome sequencing approach was used to obtain metagenomic data on faecal specimens of 36 children with ASD and 21 healthy neurotypical children of 3-5 years old. Taxonomic analysis was conducted using MetaPhlAn2. The developed bioinformatics algorithm and created catalogue of the orthologues were applied to identify bacterial genes of neuroactive compounds in the metagenomes. For the identification of metagenomic signatures of children with ASD, Wilcoxon's test and adjustment for multiple comparisons were used.Results. Statistically significant differences with decreases in average abundance in the microbiota of ASD children were found for the genera Barnesiella and Parabacteroides and species Alistipes putredinis, B. caccae, Bacteroides intestinihominis, Eubacterium rectale, Parabacteroides distasonis and Ruminococcus lactaris. Average relative abundances of the detected genes and neurometabolic signature approach did not reveal many significant differences in the metagenomes of the groups that were compared. We noted decreases in the abundance of genes linked to production of GABA, melatonine and butyric acid in the ASD metagenomes.Conclusion. For the first time, the neurometabolic signature of the gut microbiota of young children with ASD is presented. The data can help to provide a comparative assessment of the transcriptional and metabolomic activity of the identified genes.

Antibiotic Resistance Genes in the Gut Microbiota of Children with Autistic Spectrum Disorder as Possible Predictors of the Disease.

The gut microbiota (GM), which contains thousands of bacterial species, is a reservoir of antibiotic resistance genes (ARGs) called resistome. Early life exposure to antibiotics alters significantly the composition and function of the gut microbiota of children, which may trigger symptoms of autism spectrum disorder (ASD). This is because the GM plays an important role in the bidirectional communication between the gut and the brain and influences the brain normal functioning through multiple pathways. The goal of this article is to study the distribution of ARGs in the GM of 3- to 5-year-old healthy children and children with ASD living in Moscow, Russia. The metagenomic analysis of samples from both groups revealed differences in the signatures between them. The signatures consisted of the bacterial genera and aminoglycoside, ß-lactam, macrolide, and tetracycline resistance genes that they harbored. Our results show an increase in ARGs in the resistome of the GM of children with ASD. These findings emphasize the negative influence of early-life antibiotic therapy. We found three ARGs, aac(6')-aph(2''), cepA-49, and tet(40), which could serve as markers of ASD. The additional functions carried out by the enzymes, encoded by these genes, are being discussed.

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.

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.

Draft Genome Sequences of Bifidobacterium angulatum GT102 and Bifidobacterium adolescentis 150: Focusing on the Genes Potentially Involved in the Gut-Brain Axis.

The draft genome sequences of Bifidobacterium angulatum GT102 and Bifidobacterium adolescentis 150 strains isolated from the human intestinal microbiota are reported. Both strains are able to produce gamma-aminobutyric acid (GABA). Detailed genomes analysis will help to understand the role of GABA in the functioning of gut-brain axis.