KEGG Database Research Articles

CSIG-21. THE ROLE OF GUT MICROBIOTA IN GLIOBLASTOMA: INSIGHTS FROM MICROBIOME-GENE EXPRESSION INTERACTIONS

Abstract Glioblastoma, the most aggressive form of primary brain tumor, remains a formidable clinical challenge due to its invasiveness and resistance to therapy. Emerging evidence suggests that the gut microbiome plays a crucial role in modulating cancer progression through complex interactions with host physiology. In this study, we investigated the influence of gut microbiota and tumor gene expression by analyzing stool and tissue samples from glioblastoma patients. Utilizing 16S rRNA sequencing of stool samples and NanoString gene expression analysis of tumor tissue samples, we explored the relationship between gut microbiome taxa and gene expression levels in tissue. Pathway analysis using KEGG and Gene Ontology databases was employed to elucidate the functional implications of these interactions. Our findings reveal contrasting effects of specific gut microbiota taxa and gene expression, with Fusobacterium demonstrating a potential oncogenic role, while Bifidobacteriaceae and Akkermansiaceae display potential tumor-suppressive effects. Fusobacterium is associated with the upregulation of key oncogenes and pathways promoting cancer cell survival, growth, and metabolism, whereas Bifidobacteriaceae and Akkermansiaceae are linked to the downregulation of genes involved in pathways promoting cancer cell survival and proliferation, such as MAPK signaling and stress response pathways, potentially inhibiting cancer cell growth. These results highlight the intricate interplay between gut microbiota composition and cancer biology and underscore the potential of gut microbiota modulation as a therapeutic strategy in glioblastoma management.

Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico study

BackgroundUterine corpus endometrial carcinoma (UCEC), derived from the endometrium, is the most common type of endometrial malignasis. This gynecological malignancy is very common all over the world, especially in developed countries and shows a potentially rising trend correlated with the increase in obese women. MethodsDifferentially Expressed Genes (DEGs) analysis was conducted on GSE7305 and GSE25628 datasets from the Gene Expression Omnibus (GEO). DEGs were identified using GEO2R (adjusted p-value <0.05, |logFC| > 1). Pathway analysis employed KEGG and Gene Ontology databases, while protein-protein interactions were analyzed using Cytoscape and Gephi. GEPIA was used for target gene validation. ResultsWe have identified 304 common DEGs and 78 hub genes using GEO and PPI analysis, respectively. The GO and KEGG pathways analysis revealed enrichment of DEGs in extracellular matrix structural constituent, extracellular space, cell adhesion, and ECM-receptor interaction. GEPIA analysis identified three genes, ENG, GNG4, and ECT2, whose expression significantly differed between normal and tumor samples. ConclusionThis analysis study identified the hub genes and associated pathways involved in the pathogenesis of UCEC. The identified hub genes exhibit remarkable potential as diagnostic biomarkers, providing a significant opportunity for early diagnosis and more effective therapeutic approaches for UCEC.

First De Novo genome assembly and characterization of Gaultheria prostrata.

Gaultheria Kalm ex L. (Ericaceae), a type of evergreen shrub, known as a natural source of methyl salicylate, possesses rich germplasm resources, strong habitat adaptability, significant ornamental value, and noteworthy pharmacological activities. However, due to the paucity of whole genomic information, genetically deep research in these areas remains limited. Consequently, we intend to obtain genome data through high-throughput sequencing, gene annotation, flow cytometry, transcription factors prediction and genetic marker analysis for a representative species of this genus, with Gaultheria prostrata selected for our study. In this study, we preliminarily obtained the genome of G. prostrata through next-generation sequencing methods. Utilizing 47.94 Gb of high-quality sequence data (108.95× coverage), assembled into 114,436 scaffolds, with an N50 length of 33,667 bp. The genome size assembled by SOAPdenovo, approximately 417 Mb, corresponded closely to predictions by flow cytometry (440 Mb) and k-mer analysis (447 Mb). The genome integrity was evaluated using BUSCO with 91%. The heterozygosity ratio was 0.159%, the GC content was 38.85%, and the repetitive regions encompassed over 34.6% of the genome. A total of 26,497 protein-coding genes have been predicted and annotated across Nr, Swissprot, GO, KEGG, and Pfam databases. Among these, 14,377 and 2,387 genes received functional annotation in Nr and Swissprot, respectively; 21,895, 24,424, and 22,330 genes were similarly annotated in GO, KEGG, and Pfam. Moreover, A total of 279,785 SSRs were identified and 345,270 primers for these SSRs were designed. Within the various nucleotide types of SSRs, AG/CT and AAG/CTT constituted the predominant dinucleotide and trinucleotide repeat types in G. prostrata. In addition, 1,395 transcription factors (TFs) from 75 TF families, 462 transcription regulators (TRs) from 33 TR families and 840 protein kinase (PKs) from 118 PK families were identified in this genome. We also performed phylogenetic analyses of G. prostrata and related species, including estimation of divergence times and expansion and contraction analyses, followed by positive selection analyses of orthologous gene pairs of G. prostrata and its close relative Vaccinium corymbosum. These results provide a reference for in-depth study of genus Gaultheria, contributing to future functional and comparative genomics analyses and providing supporting data for the development of molecular markers.

Mining and expression analysis of color related genes in Bougainvillea glabra bracts based on transcriptome sequencing.

Bract coloration is one of the key ornamental traits in Bougainvillea, yet research has predominantly focused on phenotypic color traits and pigment composition, with limited understanding of the molecular mechanisms underlying color formation. This gap hinders the improvement and innovation in bract coloration. To elucidate the regulatory mechanisms of bract coloration in Bougainvillea and to enhance the utilization of its germplasm resources, this study employed the Illumina Novaseq 6000 sequencing platform to conduct transcriptomic sequencing on 21 samples of bracts exhibiting seven distinct phenotypes. Comparative analysis against Nr, Pfam, EggNOG, GO, and KEGG databases annotated 90,279 unigenes. The highest annotation rates were achieved with the Nr (40.13%), GO (30.44%), and EggNOG (25.64%) databases. Among the species annotated, Beta vulgaris (20.08%) and Chenopodium quinoa (14.58%) shared the highest homology with Bougainvillea bract transcriptomes. WGCNA analysis identified 12 positively correlated tissue-specific modules, of which 2 are related to bract color formation. By comparing transcriptome data and genes within these specific modules against the KEGG database, a total of 321 unigenes associated with bract color formation in Bougainvillea were discovered. Among these, 220 unigenes are involved in anthocyanin synthesis, 43 unigenes are involved in betalain synthesis, 23 unigenes are annotated as Chlorophyll a-b binding protein genes, and 35 unigenes participate in carotenoid synthesis. Quantitative real-time PCR (qRT-PCR) validation of 16 differentially expressed genes (DEGs) including PAL2, CHS1, ANS, BZ1, 6GT, CDOPA5GT, ANR, CHS2, and DOPA, revealed significant expression differences among magenta, yellow, white, and cherry-colored bracts, suggesting their potential as candidate genes for bract color development. This study not only enriches the transcriptomic data of Bougainvillea but also identifies genes associated with bract coloration, providing a valuable theoretical basis for future gene cloning, genetic engineering, and breeding efforts in Bougainvillea.

Unveiling MurM inhibitors in Enterococcus faecalis V583: a promising approach to tackle antibiotic resistance

Enterococcus faecalis is commonly found in the GI tract of humans and animals. It causes various infections, especially in hospital environments, and shows growing antibiotic resistance. This study utilized a subtractive proteomics approach to find out the potential drug targets in E. faecalis. Unique metabolic pathways were analysed and compared to the host to minimize adverse effects. Among twenty nine pathogenic specific and seventy three host-pathogen common pathways identified using the KEGG database, sixty seven essential proteins were found through the DEG BLAST search. PSORTB predicted that forty cytoplasmic proteins could be suitable as druggable targets. Further analysis identified fourteen proteins with virulence properties using the VFDB BLAST. Among these, seven proteins with more than ten antigenic sites were subjected to DrugBank BLAST, identifying three novel and four existing drug targets. One of the crucial drug targets, MurM, was selected due to its critical role in peptidoglycan biosynthesis. The reason for selecting MurM is crucial for addressing antibiotic resistance, disrupting bacterial cell wall synthesis, and attaining selective antimicrobial activity. MurM belongs to the mixed αβ class with two functional domains. The possible binding site residues of MurM are Trp31, Lys35, Trp38, Arg215, and Tyr219. Virtual screening identified potential lead candidates for MurM, and four were selected based on their physiochemical, pharmacokinetic, and structural properties. This study provides valuable insights into identifying and analysing a potential drug target, the MurM protein, and its inhibitors in E. faecalis V583.

Integrated Transcriptomics and Metabolomics Studies Reveal Steroid Biosynthesis Pathway and BCL2 Inhibitory Diazo-Progesterone of Drimia indica for Conservation and Sustainable Utilization.

This study is the first report on the sequence of the transcriptome of Drimia indica, a non-model plant with medicinal properties found in a forest tribal belt, using the Illumina NovaSeq platform. The primary objectives of this study were to elucidate the gene expression profiles in different tissues, identify key regulatory genes and pathways involved in secondary metabolite biosynthesis, and explore the plant's potential pharmacological properties. The study generated 670087 unigenes from both leaves and roots and identified putative homologs of annotated sequences against UniProt/Swiss-Prot and KEGG databases. The functional annotation of the identified unigenes revealed the secondary metabolite biosynthetic process as the most prominent pathway, with gene enrichment analysis predominantly accounting for secondary metabolite pathways, such as terpenoid, steroid, flavonoid, alkaloid, selenocompound, and cortisol synthesis. The study also identified regulatory genes NAC, Bhlh, WRKY, and C2H2 on the transcriptome dataset. The functionally annotated unigenes suggested phytocompounds in Drimia indica to have multi-potent properties, such as anti-cancer, anti-inflammatory, and anti-diabetic activities, which has been further validated by GC-MS-based metabolite profiling. Notably, we have identified two novel molecules, di-azo progesterone and 4H-pyran-4-one 2,3-dihydro-3,5-dihydroxy- 6-methyl, with potential BCL2 inhibitory anticancer properties, supported by stable binding interactions observed in molecular docking and dynamics simulations. Additionally, an abundance of mono-nucleotide SSR markers has been identified, useful for genetic diversity studies. This study provides a foundational understanding of the molecular mechanisms in Drimia indica, highlighting its potential as a source for novel therapeutic agents and contributing valuable insights for future pharmacological and agricultural applications. However, further in vivo studies are warranted to confirm these findings and validate their pharmacological efficacy and therapeutic potential. The SSR markers identified also offer valuable tools for molecular genetics, plant breeding, and sustainable drug development.

Complete genome sequence analysis and Pks genes identification of Brevibacillus brevis FJAT-0809-GLX with a broad inhibitory spectrum against phytopathogens.

Brevibacillus brevis FJAT-0809-GLX has a broad spectrum of antimicrobial activity. Understanding the molecular basis of biocontrol ability of B. brevis will allow us to develop effective microbial agents for sustainable agriculture. In this study, we present the complete and annotated genome sequence of FJAT-0809-GLX. The complete genome size of B. brevis FJAT-0809-GLX was 6,137,019bp, with 5688 predicted coding sequences (CDS). The average GC content of 47.38%, and there were 44 copies of the rRNAs operon (16S, 23S and 5S RNA), and 127 tRNA genes. A total of 11,162 genes were functionally annotated with the COG, GO, and KEGG databases, and 123 genes belonged to CAZymes. Genomic secondary metabolite analysis indicated 13 clusters encoding potential new antimicrobials. FJAT-0809-GLX was designated as B. brevis according to average nucleotide polymorphism (ANI) and phylogenetic analysis. The pangenome consisted of 7141 homologous genes, and 4469 homologous genes shared by B. brevis FJAT-0809-GLX, B. brevis NBRC100599, B. brevis DSM30, and B. brevis NCTC2611. The number of unique homologous genes of B. brevis FJAT-0809-GLX (419 genes) and B. brevis NBRC100599 (480 genes) were much more than those in B. brevis DSM30 (13 genes), and B. brevis NCTC2611 (6 genes). Nine gene clusters encoding for secondary metabolite biosynthesis were compared in the genome of B. brevis FJAT-0809-GLX with those of B. brevis NBRC100599, B. brevis DSM30 and B. brevis NCTC2611, and the gene clusters encoding for lantipeptide and transatpks-otherks only existed in genome of B. brevis FJAT-0809-GLX. The 11 BbPks genes were included in the B. brevis FJAT-0809-GLX genome, which contained the conserved PS-DH domain. The relative expression of BbPksL, BbPksM2, BbPksM3, BbPksN3, BbPksN4 and BbPksN5 reached a maximum at 120h and then decreased at 144h. Our results provided detailed genomic and Pks genes information for the FJAT-0809-GLX strain, and lid a foundation for studying its biocontrol mechanisms.

New Insights on the Glyphosate-Degrading Enzymes C-P Lyase and Glyphosate Oxidoreductase Based on Bioinformatics

Bioremediation, the degradation of environmental pollutants by living organisms, has immense potential to lead to a greener planet. Bioinformatics analysis can contribute to the identification of novel microorganisms, which biodegrade contaminants, or of participating proteins and enzymes, and the elucidation of the complex metabolic pathways involved. In this study, we focus on C-P lyase and glyphosate oxidoreductase (Gox), two enzymes which degrade glyphosate, a widely used pesticide. Amino acid sequences of the two enzymes were collected from a broad range of microorganisms using the KEGG database and BLAST. Based on this, we identified additional lineages, with putative glyphosate-degrading activity, for which no glyphosate-degrading species have been reported yet. The conserved residues in each enzyme were identified via multiple alignments and mapped onto the 3D structures of the enzymes, using PyMOL, leading to novel insights into their function. As the experimental structure of Gox is still unknown, we created structural models based on three different programs and compared the results. This approach can be used to yield insights into the characteristics of potential glyphosate-degrading enzymes. Given the limited information available, such a step is important to gain further knowledge about them, which can contribute to their application in bioremediation in the future.

The Effect of Drugs on the Intestinal Microbiota in Crohn's Disease.

We took advantage of a single-center cross-sectional study to investigate the effect of different drugs on intestinal microbiota and function in Crohn's disease. We studied the difference in fecal microbiota of Crohn's disease patients treated with mesalazine, azathioprine, and infliximab, as well as untreated patients, by metagenome and screened for differential microbiota. Further, we investigated functional differences in intestinal microbiota among the four groups. Through metagenomic sequencing, we found that there was no difference between the four groups in ACE and Chao1 indices, but IFX and mesalazine improved species diversity and homogeneity compared to the untreated group, as evidenced by statistically significant differences in the Shannon index, Simpson index, and pielou_evenness. In addition, beta diversity suggested a difference between groups, but the difference was not significant. Non-parametric tests revealed differences between the four groups at the phylum level, class level, and genus level. Further analysis by LEfSe analysis revealed that the level of short-chain fatty acid-producing microbiota was increased in the treated groups, while there was no difference between the treated groups when compared to each other. Finally, the KEGG database and EggNOG database revealed that there were functional differences in intestinal microbiota among the four groups, including microbial metabolism pathway, cysteine and methionine metabolism pathway, cytoskeleton, etc. Conclusions: Mesalazine, azathioprine, and infliximab can all affect the intestinal microbiota and function in patients with Crohn's disease, and the drugs may alleviate intestinal inflammation in patients with Crohn's disease by modulating the intestinal microbiota.

Breast cancer promotes the expression of neurotransmitter receptor related gene groups and image simulation of prognosis model

Breast cancer (BC), a prevalent and severe malignancy, detrimentally affects women globally. Its prognostic implications are profoundly influenced by gene expression patterns. This study retrieved 509 BC-associated oncogenes and 1,012 neurotransmitter receptor-related genes from the GSEA and KEGG databases, intersecting to identify 98 relevant genes. Clinical and transcriptomic expression data related to BC were downloaded from the TCGA, and differential genes were identified based on an FDR value <0.05 & |log2FC| ≥ 0.585. Univariate analysis of these genes revealed that high expression of NSF and low expression of HRAS, KIF17, and RPS6KA1 are closely associated with BC survival prognosis. A prognostic model constructed for these four genes demonstrated significant prognostic relevance for BC-TCGA patients (P < 0.001). Subsequently, an immunofunctional analysis of the BC oncogene-neurotransmitter receptor-related gene cluster revealed the involvement of immune cells such as T cells CD8, T cells CD4 memory resting, and Macrophages M2. Further analysis indicated that immune functions were primarily concentrated in APC_co_inhibition, APC_co_stimulation, CCR, and Check-point, among others. Lastly, a prognostic nomogram model was established, and ROC curve analysis revealed that the nomogram is a vital indicator for assessing BC prognosis, with 1-year, 3-year, and 5-year survival rates of 0.981, 0.897, and 0.802, respectively. This model demonstrates high calibration, clinical utility, and predictive capability, promising to offer an effective preliminary tool for clinical diagnostics.

Transcriptome Analysis Revealed the Anabolic Regulation of Chlorophyll and Carotenoids in Curcuma alismatifolia Bracts.

Curcuma alismatifolia is an attractive ornamental plant in the ginger family. Its bracts come in a variety of colors and are commonly used as cut flowers, potted plants, and landscaping. To investigate the regulation of bract pigmentation in C. alismatifolia, we examined the pigment levels of chlorophyll and carotenoids in the pure color part (PC) and variegated part (VA) of three C. alismatifolia varieties, i.e., "Siam TM Sitrone," "Chiang Mai Pink," and "Snow White." To mine the color mechanisms of the pure color and variegated parts of the bract, we conducted RNA-seq analysis on C. alismatifolia. We identified a total of 89,975 unigenes, and there were 3584 differentially expressed genes identified post-screening. Furthermore, 1858 DEGs were annotated in the GO database and 681 in the KEGG database. We pinpointed key genes responsible for the diverse bract colors in C. alismatifolia, including ZEP for carotenoid synthesis and GAGA2 in the chlorophyll synthesis pathway. This study provides valuable insights into understanding the pigmentation mechanism of bracts in C. alismatifolia and the breeding process.

Construction and characterization of DNA libraries from cultured phages and environmental viromes.

Despite many efforts to understand and leverage the functional potential of environmental viromes, most bacteriophage genes are largely uncharacterized. To explore novel biology from uncultivated microbes like phages, metagenomics has emerged as a powerful tool to directly mine new genes without the need to culture the diverse microbiota and the viruses within. When a pure computational approach cannot infer gene function, it may be necessary to create a DNA library from environmental genomic DNA, followed by the screening of that library for a particular function. However, these screens are often initiated without a metagenomic analysis of the completed DNA library being reported. Here, we describe the construction and characterization of DNA libraries from a single cultured phage (ΦT4), five cultured Escherichia coli phages, and three metagenomic viral sets built from freshwater, seawater, and wastewater samples. Through next-generation sequencing of five independent samplings of the libraries, we found a consistent number of recovered genes per replicate for each library, with many genes classifiable via the KEGG and Pharokka databases. By characterizing the size of the genes and inserts, we found that our libraries contain a median of one to two genes per contig with a median gene length of 303-381 bp for all libraries, reflective of the small genomes of viruses. The environmental libraries were genetically diverse compared to the single phage and multi-phage libraries. Additionally, we found reduced coverage of individual genomes when five phages were used as opposed to one. Taken together, this work provides a comprehensive analysis of the DNA libraries from phage genomes that can be used for metagenomic exploration and functional screens to infer and identify new biology.IMPORTANCEFunctional metagenomics is an approach that aims to characterize the putative biological function of genes in the microbial world. This includes an examination of the sequencing data collected from a pooled source of diverse microbes and inference of gene function by comparison to annotated and studied genes from public databases. At times, DNA libraries are made from these genes, and the library is screened for a specific function. Hits are validated using a combination of biological, computational, and structural analysis. Left unresolved is a detailed characterization of the library, both its diversity and content, for the purposes of imputing function entirely by computational means, a process that may yield findings that aid in designing useful screens to identify novel gene functions. In this study, we constructed libraries from cultured phages and uncultured viromes from the environment and characterized some important parameters, such as gene number, genes per contig, ratio of hypothetical to known proteins, total genomic coverage and recovery, and the effect of pooling genetic information from multiple sources, to provide a better understanding of the nature of these libraries. This work will aid the design and implementation of future screens of pooled DNA libraries to discover and isolate viral genes with novel biology across various biomes.

Identification of potential characteristic genes in chronic skin infections through RNA sequencing and immunohistochemical analysis.

The objective of the present study was to perform RNA sequencing and immunohistochemical analysis on skin specimens obtained from healthy individuals and individuals afflicted with prolonged skin infections. Bioinformatics methodologies were used to scrutinize the RNA sequencing data with the intention of pinpointing distinctive gene signatures associated with chronic skin infections. Skin tissue samples were collected from 11 individuals (4 subjects healthy and 7 patients with chronic skin infections) at the Affiliated Hospital of Southwest Medical University (Luzhou, China). The iDEP tool identified differentially expressed genes (DEGs) with log2 (fold change) ≥2 and q-value ≤0.01. Functional enrichment analysis using Gene Ontology and KEGG databases via the oebiotech online tool was then performed to determine the biological functions and pathways related to these DEGs. A protein-protein interaction network of DEGs identified HIF1A as a potential key gene. Subsequent immunohistochemistry analyses were performed on the samples to assess any variations in HIF1A expression. A total of 900 DEGs, 365 upregulated and 535 downregulated, were observed between the normal and chronic infection groups. The identified DEGs were found to serve a role in various biological processes, including 'hypoxia adaptation', 'angiogenesis', 'cell adhesion' and 'regulation of positive cell migration'. Additionally, these genes were revealed to be involved in the 'TGF-β', 'PI3K-Akt' and 'IL-17' signaling pathways. HIF1A and nine other genes were identified as central nodes in the PPI network. HIF1A expression was higher in chronically infected skin samples than in healthy samples, indicating its potential as a novel research target.

Forecasting the Pharmacological Mechanisms of Plumbago zeylanica and Solanum xanthocarpum in Diabetic Retinopathy Treatment: A Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation Study.

(1) Background: Diabetic retinopathy (DR) is a major complication of diabetes, marked by abnormal angiogenesis, microaneurysms, and retinal hemorrhages. Traditional Ayurvedic medicine advocates multi-target strategies for DR management. However, the mechanisms by which Solanum xanthocarpum (SX) and Plumbago zeylanica (PZ) exert therapeutic effects are not well understood; (2) Methods: To investigate these mechanisms, we employed network pharmacology and molecular docking techniques. Phytochemicals from SX and PZ were identified using the IMPPAT database and Swiss Target Prediction tool. DR-related protein targets were sourced from the GeneCards database, and common targets were identified through Venn diagram analysis. STRING and Cytoscape were used to construct and analyze protein-protein interaction networks. Pathway enrichment was performed with Gene Ontology and KEGG databases; (3) Results: We identified 28 active phytoconstituents, targeting proteins such as EGFR, SRC, STAT3, AKT1, and HSP90AA1. Molecular docking and dynamics simulations confirmed the strong binding affinities of these compounds to their targets; (4) Conclusions: The study highlights the multi-target activity of SX and PZ, particularly in pathways related to EGFR tyrosine kinase inhibitor resistance and PI3K-AKT signaling. These findings provide valuable insights into their therapeutic potential for DR, suggesting the effective modulation of key molecular pathways involved in the disease.

Linking gut microbiota dysbiosis to molecular pathways in Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disorder marked by cognitive decline and synaptic dysfunction. Emerging evidence suggests a significant relationship between gut microbiota and brain health, mediated through the gut-brain axis. Alterations in gut microbiota composition may influence AD progression by affecting molecular pathways and miRNA interactions. MethodsWe retrieved and analyzed microarray data from 34 tissue samples of AD patients and controls (GEO accession number GSE110298). Differentially expressed genes (DEGs) with the GCS score package in R, considering a p-value < 0.05 and logFC<-1 and logFC>1 to isolate significant gene clusters. Enrichment analysis of signaling pathways and gene ontology was conducted using Enrichr, KEGG, Panther, DAVID, and shiny GO databases. Protein-protein interactions were visualized with Networkanalyst and CytoScape. Gut microbiota in 200 CE patients was analyzed using next-generation sequencing (NGS) data from gutMDisorder and GMrepo databases. miRNA interactions were evaluated using miEAA, Targetscan, MienTurnet, and miRnet databases. ResultsSignificant reductions in microbial taxa, including Clostridia (LDA score −4.878208), Firmicutes (LDA score −4.817032), and Faecalibacterium (LDA score −4.40714), were observed in AD patients. Pathway analysis highlighted the involvement of Axon guidance, ErbB, and MAPK signaling pathways in AD. Venn diagram analysis identified 619 intersecting genes in brain and gut tissues, emphasizing pathways such as Axon Guidance and Cell Cycle. miRNA analysis revealed important regulatory miRNAs, including hsa-let-7c, hsa-mir-125b-2, and hsa-mir-145, which target key transcription factors involved in AD pathology. ConclusionThe study demonstrates significant dysbiosis in the gut microbiota of AD patients and underscores the potential role of gut microbiota in AD progression through altered signaling pathways and miRNA interactions. These findings highlight the need for further research into microbiota-based interventions as potential therapeutic strategies for AD.

Metagenomic functional profiling: to sketch or not to sketch?

Functional profiling of metagenomic samples is essential to decipher the functional capabilities of microbial communities. Traditional and more widely used functional profilers in the context of metagenomics rely on aligning reads against a known reference database. However, aligning sequencing reads against a large and fast-growing database is computationally expensive. In general, k-mer-based sketching techniques have been successfully used in metagenomics to address this bottleneck, notably in taxonomic profiling. In this work, we describe leveraging FracMinHash (implemented in sourmash, a publicly available software), a k-mer-sketching algorithm, to obtain functional profiles of metagenome samples. We show how pieces of the sourmash software (and the resulting FracMinHash sketches) can be put together in a pipeline to functionally profile a metagenomic sample. We named our pipeline fmh-funprofiler. We report that the functional profiles obtained using this pipeline demonstrate comparable completeness and better purity compared to the profiles obtained using other alignment-based methods when applied to simulated metagenomic data. We also report that fmh-funprofiler is 39-99× faster in wall-clock time, and consumes up to 40-55× less memory. Coupled with the KEGG database, this method not only replicates fundamental biological insights but also highlights novel signals from the Human Microbiome Project datasets. This fast and lightweight metagenomic functional profiler is freely available and can be accessed here: https://github.com/KoslickiLab/fmh-funprofiler. All scripts of the analyses we present in this manuscript can be found on GitHub.

Assembling bacterial puzzles: piecing together functions into microbial pathways.

Functional metagenomics enables the study of unexplored bacterial diversity, gene families, and pathways essential to microbial communities. However, discovering biological insights with these data is impeded by the scarcity of quality annotations. Here, we use a co-occurrence-based analysis of predicted microbial protein functions to uncover pathways in genomic and metagenomic biological systems. Our approach, based on phylogenetic profiles, improves the identification of functional relationships, or participation in the same biochemical pathway, between enzymes over a comparable homology-based approach. We optimized the design of our profiles to identify potential pathways using minimal data, clustered functionally related enzyme pairs into multi-enzymatic pathways, and evaluated our predictions against reference pathways in the KEGG database. We then demonstrated a novel extension of this approach to predict inter-bacterial protein interactions amongst members of a marine microbiome. Most significantly, we show our method predicts emergent biochemical pathways between known and unknown functions. Thus, our work establishes a basis for identifying the potential functional capacities of the entire metagenome, capturing previously unknown and abstract functions into discrete putative pathways.

Biodegradation of DDT using multi-species mixtures: Fromgenome-mining prediction to practical assessment.

DDT (dichlorodiphenyltrichloroethane) is a commonly used insecticide that is recalcitrant and highly stable in the environment. Currently, DDT residue contamination, especially in agricultural soil, is still a concern in many countries, threatening human health and the environment. Among the approaches to resolve such an issue, novel biodegradation-based methods are now preferred to physicochemical methods, due to the sustainability and the effectiveness of the former. In this study, we explored the possibility of building mixed microbial cultures that can offer improved DDT-degrading efficiencies and be more environmentally transilient, based on genome annotation using the KEGG database and prediction of interactions between single strains using the obtained metabolic maps. We then proposed 10 potential DDT-degrading mixed cultures of different strain combinations and evaluated their DDT degradation performances in liquid, semi-solid and solid media. The results demonstrated the superiority of the mixtures over the single strains in terms of degrading DDT, particularly in a semi-solid medium, with up to 40-50% more efficiency. Not only did the mixed cultures degrade DDT more efficiently, but they also adapted to broader spectra of environmental conditions. The three best DDT-degrading and transilient mixtures were selected, and it turned out that their component strains seemed to have more metabolic interactions than those in the other mixtures. Thus, our study demonstrates the effectiveness of exploiting genome-mining techniques and the use of constructed mixed cultures in improving biodegradation.

Starvation resilience in anammox-based bioreactors: A stable nitrogen removal route on partial denitrification/anammox (PD/A)

This study investigates the performance, resilience and microbial community dynamics of two anaerobic processes, i.e. pure anammox (R1) and partial denitrification/anammox (PD/A) (R2), following a 30-day starvation period. The tolerance to starvation was assessed by comparing nitrogen removal efficiency and microbial activity across both reactors. Results show that the PD/A process recovery to pre-starvation performance levels within just one day, as compared to the pure anammox process. Notably, although the activity of anammox bacteria decreased in both processes during starvation, the decay rate in R1 was 69.59 % higher than in R2, potentially explaining the quicker recovery of R2. Furthermore, enhanced secretion of extracellular polymeric substance (EPS) during starvation served as a protective mechanism. The potential functions and genes in microorganisms, as well as the pathway of nitrogen cycling, were demonstrated through analyses using the KEGG database. This research reveals essential mechanistic insights and strategic guidance for the effective implementation of anammox-based biological nitrogen removal processes.

Comparative transcriptome and coexpression network analysis revealed the regulatory mechanism of Astragalus cicer L. in response to salt stress

BackgroundAstragalus cicer L. is a perennial rhizomatous legume forage known for its quality, high biomass yield, and strong tolerance to saline-alkaline soils. Soil salinization is a widespread environmental pressure. To use A. cicer L. more scientifically and environmentally in agriculture and ecosystems, it is highly important to study the molecular response mechanism of A. cicer L. to salt stress.ResultsIn this study, we used RNA-seq technology and weighted gene coexpression network analysis (WGCNA) were performed. The results showed 4 key modules were closely related to the physiological response of A. cicer. L. to salt stress. The differentially expressed genes (DEGs) of key modules were mapped into the KEGG database, and found that the most abundant pathways were the plant hormone signal transduction pathway and carbon metabolism pathway. The potential regulatory networks of the cytokinin signal transduction pathway, the ethylene signal transduction pathway, and carbon metabolism related pathways were constructed according to the expression pathways of the DEGs. Seven hub genes in the key modules were selected and distributed among these pathways. They may involved in the positive regulation of cytokinin signaling and carbon metabolism in plant leaves, but limited the positive expression of ethylene signaling. Thus endowing the plant with salt tolerance in the early stage of salt stress.ConclusionsBased on the phenotypic and physiological responses of A. cicer L. to salt stress, this study constructed the gene coexpression network of potential regulation to salt stress in key modules, which provided a new reference for exploring the response mechanism of legumes to abiotic stress.