scholarly journals Transcriptome Analysis Reveals the Genes Involved in Bifidobacterium Longum FGSZY16M3 Biofilm Formation

2021 ◽  
Vol 9 (2) ◽  
pp. 385 ◽  
Author(s):  
Zongmin Liu ◽  
Lingzhi Li ◽  
Qianwen Wang ◽  
Faizan Ahmed Sadiq ◽  
Yuankun Lee ◽  
...  
Keyword(s):  
Network Analysis ◽  
Biofilm Formation ◽  
Extracellular Polymeric Substances ◽  
Molecular Mechanisms ◽  
Early Stage ◽  
Bifidobacterium Longum ◽  
Regulation Of Gene Expression ◽  
Interaction Network ◽  
Structural Development ◽  
Sequencing Analysis

Biofilm formation has evolved as an adaptive strategy for bacteria to cope with harsh environmental conditions. Currently, little is known about the molecular mechanisms of biofilm formation in bifidobacteria. A time series transcriptome sequencing analysis of both biofilm and planktonic cells of Bifidobacterium longum FGSZY16M3 was performed to identify candidate genes involved in biofilm formation. Protein–protein interaction network analysis of 1296 differentially expressed genes during biofilm formation yielded 15 clusters of highly interconnected nodes, indicating that genes related to the SOS response (dnaK, groS, guaB, ruvA, recA, radA, recN, recF, pstA, and sufD) associated with the early stage of biofilm formation. Genes involved in extracellular polymeric substances were upregulated (epsH, epsK, efp, frr, pheT, rfbA, rfbJ, rfbP, rpmF, secY and yidC) in the stage of biofilm maturation. To further investigate the genes related to biofilm formation, weighted gene co-expression network analysis (WGCNA) was performed with 2032 transcript genes, leading to the identification of nine WGCNA modules and 133 genes associated with response to stress, regulation of gene expression, quorum sensing, and two-component system. These results indicate that biofilm formation in B. longum is a multifactorial process, involving stress response, structural development, and regulatory processes.

scholarly journals Molecular Mechanisms Underpinning Aggregation in Acidiphilium sp. C61 Isolated from Iron-Rich Pelagic Aggregates

2020 ◽  
Vol 8 (3) ◽  
pp. 314
Author(s):  
Qianqian Li ◽  
Rebecca E. Cooper ◽  
Carl-Eric Wegner ◽  
Kirsten Küsel
Keyword(s):  
Hot Spots ◽  
Biofilm Formation ◽  
Extracellular Polymeric Substances ◽  
Molecular Mechanisms ◽  
Core Genome ◽  
Gene Clusters ◽  
Microbial Interactions ◽  
Aggregate Formation ◽  
Rna Seq ◽  
Metabolic Potential

Iron-rich pelagic aggregates (iron snow) are hot spots for microbial interactions. Using iron snow isolates, we previously demonstrated that the iron-oxidizer Acidithrix sp. C25 triggers Acidiphilium sp. C61 aggregation by producing the infochemical 2-phenethylamine (PEA). Here, we showed slightly enhanced aggregate formation in the presence of PEA on different Acidiphilium spp. but not other iron-snow microorganisms, including Acidocella sp. C78 and Ferrovum sp. PN-J47. Next, we sequenced the Acidiphilium sp. C61 genome to reconstruct its metabolic potential. Pangenome analyses of Acidiphilium spp. genomes revealed the core genome contained 65 gene clusters associated with aggregation, including autoaggregation, motility, and biofilm formation. Screening the Acidiphilium sp. C61 genome revealed the presence of autotransporter, flagellar, and extracellular polymeric substances (EPS) production genes. RNA-seq analyses of Acidiphilium sp. C61 incubations (+/− 10 µM PEA) indicated genes involved in energy production, respiration, and genetic processing were the most upregulated differentially expressed genes in the presence of PEA. Additionally, genes involved in flagellar basal body synthesis were highly upregulated, whereas the expression pattern of biofilm formation-related genes was inconclusive. Our data shows aggregation is a common trait among Acidiphilium spp. and PEA stimulates the central cellular metabolism, potentially advantageous in aggregates rapidly falling through the water column.

scholarly journals Development and Validation of Novel Biomarkers Related to M2 Macrophages Infiltration by Weighted Gene Co-Expression Network Analysis in Prostate Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Ning Xu ◽  
Ru-Nan Dong ◽  
Ting-Ting Lin ◽  
Tian Lin ◽  
Yun-Zhi Lin ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Network Analysis ◽  
Functional Annotation ◽  
Molecular Mechanisms ◽  
Cancer Genomics ◽  
Interaction Network ◽  
The Cancer Genome Atlas ◽  
Pathway Enrichment Analysis ◽  
Castration Resistance ◽  
Hub Genes

M2-tumor-associated macrophages (TAMs) work as a promoter in the processes of bone metastases, chemotherapy resistance, and castration resistance in prostate cancer (PCa), but how M2-TAMs affect PCa has not been fully understood. In this study, we analyzed the proportion of tumor-infiltrating immune cells using the CIBERSORT algorithm, based on samples from the Cancer Genome Atlas database. Then we performed weighted gene co-expression network analysis to examine the modules concerning infiltrated M2-TAMs. Gene Ontology analysis and pathway enrichment analysis were performed for functional annotation and a protein–protein interaction network was constructed. The International Cancer Genomics Consortium cohort was used as a validation cohort. The red module showed the most correlation with M2-TAMs in PCa. Biological processes and pathways were mainly associated with the immune-related processes, as revealed by functional annotation. Four hub genes were screened: ACSL1, DLGAP5, KIF23 and NCAPG. Further validation showed that the four hub genes had a higher expression level in tumor tissues than that in normal tissues, and they were good prognosis biomarkers for PCa. In conclusion, these findings contribute to understanding the underlying molecular mechanisms of how M2-TAMs affect PCa, and looking for the potential biomarkers and therapeutic targets for PCa patients.

scholarly journals Flagellar Motility Is Critical for Listeria monocytogenes Biofilm Formation

2007 ◽  
Vol 189 (12) ◽  
pp. 4418-4424 ◽  
Author(s):  
Katherine P. Lemon ◽  
Darren E. Higgins ◽  
Roberto Kolter
Keyword(s):  
Listeria Monocytogenes ◽  
Biofilm Formation ◽  
Molecular Mechanisms ◽  
Early Stage ◽  
Food Contamination ◽  
Initial Surface ◽  
Flagellar Motility ◽  
Surface Attachment ◽  
Abiotic Surfaces ◽  
Biofilm Development

ABSTRACT The food-borne pathogen Listeria monocytogenes attaches to environmental surfaces and forms biofilms that can be a source of food contamination, yet little is known about the molecular mechanisms of its biofilm development. We observed that nonmotile mutants were defective in biofilm formation. To investigate how flagella might function during biofilm formation, we compared the wild type with flagellum-minus and paralyzed-flagellum mutants. Both nonmotile mutants were defective in biofilm development, presumably at an early stage, as they were also defective in attachment to glass during the first few hours of surface exposure. This attachment defect could be significantly overcome by providing exogenous movement toward the surface via centrifugation. However, this centrifugation did not restore mature biofilm formation. Our results indicate that it is flagellum-mediated motility that is critical for both initial surface attachment and subsequent biofilm formation. Also, any role for L. monocytogenes flagella as adhesins on abiotic surfaces appears to be either minimal or motility dependent under the conditions we examined.

scholarly journals Weighted Correlation Gene Network Analysis Reveals New Potential Mechanisms and Biomarkers in Non-obstructive Azoospermia

2021 ◽  
Vol 12 ◽  
Author(s):  
Meng Dong ◽  
Hao Li ◽  
Xue Zhang ◽  
Jichun Tan
Keyword(s):  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Differential Expression Analysis ◽  
Interaction Network ◽  
Severe Form ◽  
Differentially Expressed ◽  
Obstructive Azoospermia ◽  
Oocyte Meiosis ◽  
Limma Package

Non-obstructive azoospermia (NOA) denotes a severe form of male infertility, whose etiology is still poorly understood. This is mainly due to limited knowledge on the molecular mechanisms that lead to spermatogenesis failure. In this study, we acquired microarray data from GEO DataSets and identified differentially expressed genes using the limma package in R. We identified 1,261 differentially expressed genes between non-obstructive and obstructive azoospermia. Analysis of their possible biological functions and related signaling pathways using the cluster profiler package revealed an enrichment of genes involved in germ cell development, cilium organization, and oocyte meiosis. Immune infiltration analysis indicated that macrophages were the most significant immune component of NOA, cooperating with mast cells and natural killer cells. The weighted gene coexpression network analysis algorithm generated three related functional modules, which correlated closely with clinical parameters derived from histopathological subtypes of NOA. The resulting data enabled the construction of a protein–protein interaction network of these three modules, with CDK1, CDC20, CCNB1, CCNB2, and MAD2L1 identified as hub genes. This study provides the basis for further investigation of the molecular mechanism underlying NOA, as well as indications about potential biomarkers and therapeutic targets of NOA. Finally, using tissues containing different tissue types for differential expression analysis can reflect the expression differences in different tissues to a certain extent. But this difference in expression is only related and not causal. The specific causality needs to be verified later.

scholarly journals Linking flow velocity-regulated EPS production with early-stage biofilm formation in drinking water distribution systems

2020 ◽  
Vol 20 (4) ◽  
pp. 1253-1263
Author(s):  
Yanyan Liu ◽  
Rongrong Shan ◽  
Guowei Chen ◽  
Li Liu
Keyword(s):  
Drinking Water ◽  
Flow Velocity ◽  
Biofilm Formation ◽  
Distribution Systems ◽  
Water Distribution ◽  
Extracellular Polymeric Substances ◽  
Early Stage ◽  
Water Distribution Systems ◽  
Drinking Water Distribution Systems ◽  
Drinking Water Distribution

Abstract Hydrodynamics impacts interactions between microbes and their micro-habitats in aqueous systems, thus the study of hydrodynamics is key to understanding the formation and dynamics of biofilms. Yet mechanisms of how microbial responses to hydrodynamics regulate biofilm formation in drinking water distribution systems (DWDS) are underappreciated. Here, we investigated the linkage between early-stage biofilm formation and flow velocity fluctuations in a model DWDS. Results showed that an intermediate velocity (1.0 m/s) enhanced biofilm formation, with the highest biofilm/total cells ratio of 96.91% ± 2.26%. Moreover, the intermediate velocity promoted extracellular polymeric substances (EPS) release, accompanied with lowered zeta potential and elevated hydrophobicity of suspended cells, which could be responsible for surface aggregation. Shifts in biofilm community were observed along with hydrodynamics fluctuations. Intermediate velocity (1.0 m/s) stimulated the dominance of Proteobacteria (78.16%) along with the genus predominance of Pseudomonas, known to secrete large amounts of EPS favoring biofilm formation. Overall, this study provides new understanding of biofilm formation responding to hydrodynamic fluctuations in DWDS.

scholarly journals Identification of biomarkers associated with metabolic cardiovascular disease using mRNA-SNP-miRNA regulatory network analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhiyuan Fan ◽  
Wenjuan Peng ◽  
Zhiwen Wang ◽  
Ling Zhang ◽  
Kuo Liu
Keyword(s):  
Cardiovascular Disease ◽  
Molecular Mechanisms ◽  
Early Stage ◽  
Expression Profiles ◽  
Interaction Network ◽  
Cell Receptor ◽  
Differentially Expressed ◽  
Eqtl Analysis ◽  
Nucleotide Polymorphisms ◽  
Illumina Hiseq

Abstract Background CVD is the leading cause of death in T2DM patients. However, few biomarkers have been identified to detect and diagnose CVD in the early stage of T2DM. The aim of our study was to identify the important mRNAs, micro (mi)RNAs and SNPs (single nucleotide polymorphisms) that are associated with metabolic cardiovascular disease. Materials and methods Expression profiles and GWAS data were obtained from Gene Expression Omnibus (GEO) database. MiRNA-sequencing was conducted by Illumina HiSeq 2000 platform in T2DM patients and T2DM with CVD patients. EQTL analysis and gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. MRNA-miRNA co-expression network and mRNA-SNP-miRNA interaction network were established and visualized by Cytoscape 3.7.2. Results In our study, we identified 56 genes and 16 miRNAs that were significantly differentially expressed. KEGG analyses results indicated that B cell receptor signaling pathway and hematopoietic cell lineage were included in the biological functions of differentially expressed genes. MRNA-miRNA co-expression network and mRNA-SNP-miRNA interaction network illustrated that let-7i-5p, RASGRP3, KRT1 and CEP41 may be potential biomarkers for the early detection and diagnosis of CVD in T2DM patients. Conclusion Our results suggested that downregulated let-7i-5p, and upregulated RASGRP3, KRT1 and CEP41 may play crucial roles in molecular mechanisms underlying the initiation and development of CVD in T2DM patients.

scholarly journals Transcriptome Research of Key Modules and Hub Genes Associated with Primary Myelofibrosis by Weighted Co-expression Network Analysis.

2020 ◽  
Author(s):  
Weihang Li ◽  
Bin Yuan ◽  
Shilei Zhang ◽  
Ziyi Ding ◽  
Yingjing Zhao ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Network Analysis ◽  
Early Stage ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Primary Myelofibrosis ◽  
Gene Set Enrichment Analysis ◽  
Hub Genes

Abstract Background: This study aimed to identify novel targets of diagnosis, therapy as well as prognosis for primary myelofibrosis (PMF).Methods: The gene expression profiles of GSE26049 was obtained from GEO dataset, weighted gene co-expression network analysis (WGCNA) was then performed to identify the most related modules with PMF. Subsequently, GO (Gene Ontology), KEGG (Kyoto Encyclopedia Genes and Genomes), GSEA (Gene Set Enrichment Analysis) and PPI (Protein-Protein Interaction) network were conducted to fully understand the detailed information of the green module.Results: Green module was strongly correlated with PMF disease after WGCNA analysis. 20 genes in green module were identified as hub genes responsible for the progression of PMF. Functional annotation and pathway analysis revealed that these hub genes were primarily enriched in erythrocyte differentiation, transcription factor binding, hemoglobin complex, transcription factor complex and cell cycle et al. Of which, EPB42, CALR, SLC4A1 and MPL had the most correlations with PMF.Conclusions: This study elucidated that genes EPB42, CALR, SLC4A1 and MPL were significantly more highly expressed in PMF samples than in normal samples. These four genes may be considered candidate prognostic biomarkers and potential therapeutic targets for early stage of PMF. Meanwhile, EPB42 and SLC4A1 were firstly found to be highly correlated with the progression of PMF.

Identification of biomarkers associated with metabolic cardiovascular disease using mRNA-SNP-miRNA regulatory network analysis

2021 ◽  
Author(s):  
Zhiyuan Fan ◽  
Wenjuan Peng ◽  
Zhiwen Wang ◽  
ling Zhang ◽  
Kuo Liu
Keyword(s):  
Cardiovascular Disease ◽  
Molecular Mechanisms ◽  
Early Stage ◽  
Expression Profiles ◽  
Interaction Network ◽  
Cell Receptor ◽  
Differentially Expressed ◽  
Eqtl Analysis ◽  
Nucleotide Polymorphisms ◽  
Illumina Hiseq

Abstract Background: CVD is the leading cause of death in T2DM patients. However, few biomarkers have been identified to detect and diagnose CVD in the early stage of T2DM. The aim of our study was to identify the important mRNAs, micro (mi)RNAs and SNPs (single nucleotide polymorphisms) that are associated with metabolic cardiovascular disease. Materials and methods: Expression profiles and GWAS data were obtained from Gene Expression Omnibus (GEO) database. MiRNA-sequencing was conducted by Illumina HiSeq 2000 platform in T2DM patients and T2DM with CVD patients. EQTL analysis and gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. MRNA-miRNA co-expression network and mRNA-SNP-miRNA interaction network were established and visualized by Cytoscape 3.7.2.Results: In our study, we identified 56 genes and 16 miRNAs that were significantly differentially expressed. GO and KEGG analyses results indicated that B cell receptor signaling pathway and hematopoietic cell lineage were included in the biological functions of differentially expressed genes. MRNA-miRNA co-expression network and mRNA-SNP-miRNA interaction network illustrated that let-7i-5p, RASGRP3, KRT1 and CEP41 may be potential biomarkers for the early detection and diagnosis of CVD in T2DM patients.Conclusion: Our results suggested that downregulated let-7i-5p, and upregulated RASGRP3, KRT1 and CEP41 may play crucial roles in molecular mechanisms underlying the initiation and development of CVD in T2DM patients.

Process Description of an Unconventional Biofilm Formation by Bacterial Cells Autoagglutinating Through Sticky, Long, and Peritrichate Nanofibers

2019 ◽  
Author(s):  
Yoshihide Furuichi ◽  
Shogo Yoshimoto ◽  
Tomohiro Inaba ◽  
Nobuhiko Nomura ◽  
Katsutoshi Hori
Keyword(s):  
Formation Process ◽  
Biofilm Formation ◽  
Extracellular Polymeric Substances ◽  
Waste Treatment ◽  
Large Cell ◽  
Dlvo Theory ◽  
Bacterial Cells ◽  
Chemical Production ◽  
Discontinuous Surface ◽  
Cell Cell

<p></p><p>Biofilms are used in environmental biotechnologies including waste treatment and environmentally friendly chemical production. Understanding the mechanisms of biofilm formation is essential to control microbial behavior and improve environmental biotechnologies. <i>Acinetobacter </i>sp. Tol 5 autoagglutinate through the interaction of the long, peritrichate nanofiber protein AtaA, a trimeric autotransporter adhesin. Using AtaA, without cell growth or the production of extracellular polymeric substances, Tol 5 cells quickly form an unconventional biofilm. In this study, we investigated the formation process of this unconventional biofilm, which started with cell–cell interactions, proceeded to cell clumping, and led to the formation of large cell aggregates. The cell–cell interaction was described by DLVO theory based on a new concept, which considers two independent interactions between two cell bodies and between two AtaA fiber tips forming a virtual discontinuous surface. If cell bodies cannot collide owing to an energy barrier at low ionic strengths but approach within the interactive distance of AtaA fibers, cells can agglutinate through their contact. Cell clumping proceeds following the cluster–cluster aggregation model, and an unconventional biofilm containing void spaces and a fractal nature develops. Understanding its formation process would extend the utilization of various types of biofilms, enhancing environmental biotechnologies.</p><p></p>

Lighting a path: genetic studies pinpoint neurodevelopmental mechanisms in autism and related disorders

2012 ◽  
Vol 14 (3) ◽  
pp. 239-252
Keyword(s):  
Molecular Mechanisms ◽  
Protein Localization ◽  
Regulation Of Gene Expression ◽  
Neuronal Cell ◽  
Mrna Splicing ◽  
Genetic Mutations ◽  
Scaffolding Proteins ◽  
Molecular Processes ◽  
Genetic Studies ◽  
Novel Treatments

In this review, we outline critical molecular processes that have been implicated by discovery of genetic mutations in autism. These mechanisms need to be mapped onto the neurodevelopment step(s) gone awry that may be associated with cause in autism. Molecular mechanisms include: (i) regulation of gene expression; (ii) pre-mRNA splicing; (iii) protein localization, translation, and turnover; (iv) synaptic transmission; (v) cell signaling; (vi) the functions of cytoskeletal and scaffolding proteins; and (vii) the function of neuronal cell adhesion molecules. While the molecular mechanisms appear broad, they may converge on only one of a few steps during neurodevelopment that perturbs the structure, function, and/or plasticity of neuronal circuitry. While there are many genetic mutations involved, novel treatments may need to target only one of few developmental mechanisms.

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