Comparing microarrays and next-generation sequencing technologies for microbial ecology research

CyanoStrainChip: A Novel DNA Microarray Tool for High-Throughput Detection of Environmental Cyanobacteria at the Strain Level

Detecting cyanobacteria in environments is an important concern due to their crucial roles in ecosystems, and they can form blooms with the potential to harm humans and nonhuman entities. However, the most widely used methods for high-throughput detection of environmental cyanobacteria, such as 16S rRNA sequencing, typically provide above-species-level resolution, thereby disregarding intraspecific variation. To address this, we developed a novel DNA microarray tool, termed the CyanoStrainChip, that enables strain-level comprehensive profiling of environmental cyanobacteria. The CyanoStrainChip was designed to target 1277 strains; nearly all major groups of cyanobacteria are included by implementing 43,666 genome-wide, strain-specific probes. It demonstrated strong specificity by in vitro mock community experiments. The high correlation (Pearson's R > 0.97) between probe fluorescence intensities and the corresponding DNA amounts (ranging from 1-100 ng) indicated excellent quantitative capability. Consistent cyanobacterial profiles of field samples were observed by both the CyanoStrainChip and next-generation sequencing methods. Furthermore, CyanoStrainChip analysis of surface water samples in Lake Chaohu uncovered a high intraspecific variation of abundance change within the genus Microcystis between different severity levels of cyanobacterial blooms, highlighting two toxic Microcystis strains that are of critical concern for Lake Chaohu harmful blooms suppression. Overall, these results suggest a potential for CyanoStrainChip as a valuable tool for cyanobacterial ecological research and harmful bloom monitoring to supplement existing techniques.

Pesticide-tolerant microbial consortia: Potential candidates for remediation/clean-up of pesticide-contaminated agricultural soil

Reclamation of pesticide-polluted lands has long been a difficult endeavour. The use of synthetic pesticides could not be restricted due to rising agricultural demand. Pesticide toxicity has become a pressing agronomic problem due to its adverse impact on agroecosystems, agricultural output, and consequently food security and safety. Among different techniques used for the reclamation of pesticide-polluted sites, microbial bioremediation is an eco-friendly approach, which focuses on the application of resilient plant growth promoting rhizobacteria (PGPR) that may transform or degrade chemical pesticides to innocuous forms. Such pesticide-resilient PGPR has demonstrated favourable effects on soil-plant systems, even in pesticide-contaminated environments, by degrading pesticides, providing macro-and micronutrients, and secreting active but variable secondary metabolites like-phytohormones, siderophores, ACC deaminase, etc. This review critically aims to advance mechanistic understanding related to the reduction of phytotoxicity of pesticides via the use of microbe-mediated remediation techniques leading to crop optimization in pesticide-stressed soils. The literature surveyed and data presented herein are extremely useful, offering agronomists-and crop protectionists microbes-assisted remedial strategies for affordably enhancing crop productivity in pesticide-stressed soils.

Foodomics-Based Approaches Shed Light on the Potential Protective Effects of Polyphenols in Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a chronic and progressive inflammatory disorder affecting the gastrointestinal tract (GT) caused by a wide range of genetic, microbial, and environmental factors. IBD is characterized by chronic inflammation and decreased gut microbial diversity, dysbiosis, with a lower number of beneficial bacteria and a concomitant increase in pathogenic species. It is well known that dysbiosis is closely related to the induction of inflammation and oxidative stress, the latter caused by an imbalance between reactive oxygen species (ROS) production and cellular antioxidant capacity, leading to cellular ROS accumulation. ROS are responsible for intestinal epithelium oxidative damage and the increased intestinal permeability found in IBD patients, and their reduction could represent a potential therapeutic strategy to limit IBD progression and alleviate its symptoms. Recent evidence has highlighted that dietary polyphenols, the natural antioxidants, can maintain redox equilibrium in the GT, preventing gut dysbiosis, intestinal epithelium damage, and radical inflammatory responses. Here, we suggest that the relatively new foodomics approaches, together with new technologies for promoting the antioxidative properties of dietary polyphenols, including novel delivery systems, chemical modifications, and combination strategies, may provide critical insights to determine the clinical value of polyphenols for IBD therapy and a comprehensive perspective for implementing natural antioxidants as potential IBD candidate treatment.

A Comprehensive Review of Performance of Next-Generation Sequencing Platforms

Background

Next-generation sequencing methods have been developed and proposed to investigate any query in genomics or clinical activity involving DNA. Technical advancement in these sequencing methods has enhanced sequencing volume to several billion nucleotides within a very short time and low cost. During the last few years, the usage of the latest DNA sequencing platforms in a large number of research projects helped to improve the sequencing methods and technologies, thus enabling a wide variety of research/review publications and applications of sequencing technologies.

Objective

The proposed study is aimed at highlighting the most fast and accurate NGS instruments developed by various companies by comparing output per hour, quality of the reads, maximum read length, reads per run, and their applications in various domains. This will help research institutions and biological/clinical laboratories to choose the sequencing instrument best suited to their environment. The end users will have a general overview about the history of the sequencing technologies, latest developments, and improvements made in the sequencing technologies till now.

Results

The proposed study, based on previous studies and manufacturers' descriptions, highlighted that in terms of output per hour, Nanopore PromethION outperformed all sequencers. BGI was on the second position, and Illumina was on the third position.

Conclusion

The proposed study investigated various sequencing instruments and highlighted that, overall, Nanopore PromethION is the fastest sequencing approach. BGI and Nanopore can beat Illumina, which is currently the most popular sequencing company. With respect to quality, Ion Torrent NGS instruments are on the top of the list, Illumina is on the second position, and BGI DNB is on the third position. Secondly, memory- and time-saving algorithms and databases need to be developed to analyze data produced by the 3rd- and 4th-generation sequencing methods. This study will help people to adopt the best suited sequencing platform for their research work, clinical or diagnostic activities.

A computational approach to biological pathogenicity

The current pandemic (COVID-19) has made evident the need to approach pathogenicity from a deeper and more systematic perspective that might lead to methodologies to quickly predict new strains of microbes that could be pathogenic to humans. Here we propose as a solution a general and principled definition of pathogenicity that can be practically implemented in operational ways in a framework for characterizing and assessing the (degree of) potential pathogenicity of a microbe to a given host (e.g., a human individual) just based on DNA biomarkers, and to the point of predicting its impact on a host a priori to a meaningful degree of accuracy. The definition is based on basic biochemistry, the Gibbs free Energy of duplex formation between oligonucleotides and some deep structural properties of DNA revealed by an approximation with certain properties. We propose two operational tests based on the nearest neighbor (NN) model of the Gibbs Energy and an approximating metric (the h-distance.) Quality assessments demonstrate that these tests predict pathogenicity with an accuracy of over 80%, and sensitivity and specificity over 90%. Other tests obtained by training machine learning models on deep features extracted from DNA sequences yield scores of 90% for accuracy, 100% for sensitivity and 80% for specificity. These results hint towards the possibility of an operational, objective, and general conceptual framework for prior identification of pathogens and their impact without the cost of death or sickness in a host (e.g., humans.) Consequently, a reasonable prediction of possible pathogens might pave the way to eventually transform the way we handle and prepare for future pandemic events and mitigate the adverse impact on human health, while reducing the number of clinical trials to obtain similar results.

Degradation of Xenobiotic Pollutants: An Environmentally Sustainable Approach

The ability of microorganisms to detoxify xenobiotic compounds allows them to thrive in a toxic environment using carbon, phosphorus, sulfur, and nitrogen from the available sources. Biotransformation is the most effective and useful metabolic process to degrade xenobiotic compounds. Microorganisms have an exceptional ability due to particular genes, enzymes, and degradative mechanisms. Microorganisms such as bacteria and fungi have unique properties that enable them to partially or completely metabolize the xenobiotic substances in various ecosystems.There are many cutting-edge approaches available to understand the molecular mechanism of degradative processes and pathways to decontaminate or change the core structure of xenobiotics in nature. These methods examine microorganisms, their metabolic machinery, novel proteins, and catabolic genes. This article addresses recent advances and current trends to characterize the catabolic genes, enzymes and the techniques involved in combating the threat of xenobiotic compounds using an eco-friendly approach.

Overview of Transcriptomic Research on Type 2 Diabetes: Challenges and Perspectives

Type 2 diabetes (T2D) is a common chronic disease whose etiology is known to have a strong genetic component. Standard genetic approaches, although allowing for the detection of a number of gene variants associated with the disease as well as differentially expressed genes, cannot fully explain the hereditary factor in T2D. The explosive growth in the genomic sequencing technologies over the last decades provided an exceptional impetus for transcriptomic studies and new approaches to gene expression measurement, such as RNA-sequencing (RNA-seq) and single-cell technologies. The transcriptomic analysis has the potential to find new biomarkers to identify risk groups for developing T2D and its microvascular and macrovascular complications, which will significantly affect the strategies for early diagnosis, treatment, and preventing the development of complications. In this article, we focused on transcriptomic studies conducted using expression arrays, RNA-seq, and single-cell sequencing to highlight recent findings related to T2D and challenges associated with transcriptome experiments.

The R Language: An Engine for Bioinformatics and Data Science

The R programming language is approaching its 30th birthday, and in the last three decades it has achieved a prominent role in statistics, bioinformatics, and data science in general. It currently ranks among the top 10 most popular languages worldwide, and its community has produced tens of thousands of extensions and packages, with scopes ranging from machine learning to transcriptome data analysis. In this review, we provide an historical chronicle of how R became what it is today, describing all its current features and capabilities. We also illustrate the major tools of R, such as the current R editors and integrated development environments (IDEs), the R Shiny web server, the R methods for machine learning, and its relationship with other programming languages. We also discuss the role of R in science in general as a driver for reproducibility. Overall, we hope to provide both a complete snapshot of R today and a practical compendium of the major features and applications of this programming language.

Using MMRFBiolinks R-Package for Discovering Prognostic Markers in Multiple Myeloma

Multiple myeloma (MM) is the second most frequent hematological malignancy in the world although the related pathogenesis remains unclear. Gene profiling studies, commonly carried out through next-generation sequencing (NGS) and Microarrays technologies, represent powerful tools for discovering prognostic markers in MM. NGS technologies have made great leaps forward both economically and technically gaining in popularity. As NGS techniques becomes simpler and cheaper, researchers choose NGS over microarrays for more of their genomic applications. However, Microarrays still provide significant benefits with respect to NGS. For instance, RNA-Seq requires more complex bioinformatic analysis with respect to Microarray as well as it lacks of standardized protocols for analysis. Therefore, a synergy between the two technologies may be well expected in the future. In order to take up this challenge, a valid tool for integrative analysis of MM data retrieved through NGS techniques is MMRFBiolinks, a new R package for integrating and analyzing datasets from the Multiple Myeloma Research Foundation (MMRF) CoMMpass (Clinical Outcomes in MM to Personal Assessment of Genetic Profile) study, available at MMRF Researcher Gateway (MMRF-RG), and at the National Cancer Institute Genomic Data Commons (NCI-GDC) Data Portal. Instead of developing a completely new package from scratch, we decided to leverage TC-GABiolinks, an R/Bioconductor package, because it provides some useful methods to access and analyze MMRF-CoMMpass data. An integrative analysis workflow based on the usage of MMRFBiolinks is illustrated.In particular, it leads towards a comparative analysis of RNA-Seq data stored at GDC Data Portal that allows to carry out a Kaplan Meier (KM ) Survival Analysis and an enrichment analysis for a Differential Gene Expression (DGE) gene set.Furthermore, it deals with MMRF-RG data for analyzing the correlation between canonical variants and treatment outcome as well as treatment class. In order to show the potential of the workflow, we present two case studies. The former deals with data of MM Bone Marrow sample types available at GDC Data Portal. The latter deals with MMRF-RG data for analyzing the correlation between canonical variants in a gene set obtained from the case study 1 and the treatment outcome as well as the treatment class.

What sequencing technologies can teach us about innate immunity

For years, we have taken a reductionist approach to understanding gene regulation through the study of one gene in one cell at a time. While this approach has been fruitful it is laborious and fails to provide a global picture of what is occurring in complex situations involving tightly coordinated immune responses. The emergence of whole-genome techniques provides a system-level view of a response and can provide a plethora of information on events occurring in a cell from gene expression changes to splicing changes and chemical modifications. As with any technology, this often results in more questions than answers, but this wealth of knowledge is providing us with an unprecedented view of what occurs inside our cells during an immune response. In this review, we will discuss the current RNA-sequencing technologies and what they are helping us learn about the innate immune system.

Employing gene chip technology for monitoring and assessing soil heavy metal pollution

Soil heavy metals pollution can cause many serious environment problems because of involving a very complex pollution process for soil health. Therefore, it is very important to explore methods that can effectively evaluate heavy metal pollution. Researchers were actively looking for new ideas and new methods for evaluating and predicting levels of soil heavy metal pollution. The study on microbial communities is one of the effective methods using gene chip technology. Gene chip technology, as a high-throughput metagenomics analysis technique, has been widely used for studying the structure and function of complex microbial communities in different polluted environments from different pollutants, including the soil polluted by heavy metals. However, there is still a lack of a systematic summarization for the polluted soil by heavy metals. This paper systematically analyzed soil heavy metals pollution via reviewing previous studies on applying gene chip technology, including single species, tolerance mechanisms, enrichment mechanisms, anticipation and evaluation of soil remediation, and multi-directional analysis. The latest gene chip technologies and corresponding application cases for discovering critical species and functional genes via analyzing microbial communities and evaluating heavy metal pollution of soil were also introduced in this paper. This article can provide scientific guidance for researchers actively investigating the soil polluted by heavy metals.

Absent in melanoma 1-like (AIM1L) serves as a novel candidate for overall survival in hepatocellular carcinoma

Identifying biomarkers for hepatocellular carcinoma (HCC) survival is of great importance for the early detection, monitoring, and predicting for prognosis. This study aimed to investigate the candidate biomarkers for predicting overall survival (OS) in HCC patients. Using RTCGAToolbox, top 50 upregulated differential expressed genes (DEGs) were identified. The least absolute shrinkage and selection operator (LASSO) and Cox models were used to select powerful candidate genes, and log rank method was used to address the survivor functions of potential biomarkers. Selected by LASSO model, ANLN, TTK, AIM1L and person neoplasm cancer status might be candidate parameters associated with OS in HCC patients. After adjusting person neoplasm cancer status, ANLN and TTK levels in Cox model, AIM1L was identified as a risk factor for predicting OS in HCC patients (HR = 1.5, P = 0.037). Validated in The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) series, AIM1L was significantly overexpressed in tumor tissues compared to nontumor tissues (all P < 0.0001). HCC patients with high AIM1L in tumor tissues had significantly unfavorable OS compared to those with low AIM1L in TCGA, ICGC, Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier Plotter datasets (all P < 0.05). Conclusively, AIM1L is upregulated in tumor samples and serves as a novel candidate for predicting unfavorable OS in HCC patients.

Simultaneous amplicon analysis of multiple soil samples using MinION sequencing

The diversity and composition of soil microorganisms needs to be understood as they influence ecosystem processes. MinION is a relatively recent next-generation sequencer, which provides the advantage of sequencing long reads. In this study, two types of soil were prepared experimentally to investigate the possibility of simultaneously analyzing multiple environmental samples using MinION. The MinION sequencing of amplicons was adjusted by the different rounds of PCR performed. Soil fungi and bacteria were compared using ITS and 16S rRNA amplicons, respectively. For ITS, the number of reads available for MinION sequencing were simply increased by performing two PCRs and purification using Agencourt AMPure XP. However, the effect of performing PCR twice was not high for 16S rRNA. Therefore, performing PCR twice appears to be effective for analyzing ITS regions. Regarding the number of reads obtained using MinION sequencing, clustering the same sample was possible if a read of ∼2000 bases or more was obtained in 16S rRNA and ITS. Further, information on 80 samples was obtained by performing only one round of MinION sequencing. Thus, MinION sequencing can be used to analyze a large number of samples simultaneously, providing a strong tool for amplicon sequencing. • Soil microbial composition before and after treatment was compared between 16S rRNA and ITS amplicons using MinION sequencing • One PCR amplification and two PCR amplifications were also compared • Information on 80 samples was obtained by performing only one round of MinION sequencing.

OrtSuite: from genomes to prediction of microbial interactions within targeted ecosystem processes

OrtSuite predicts synergistic species interactions using the genomic potential of microbial communities

The high complexity found in microbial communities makes the identification of microbial interactions challenging. To address this challenge, we present OrtSuite, a flexible workflow to predict putative microbial interactions based on genomic content of microbial communities and targeted to specific ecosystem processes. The pipeline is composed of three user-friendly bash commands. OrtSuite combines ortholog clustering with genome annotation strategies limited to user-defined sets of functions allowing for hypothesis-driven data analysis such as assessing microbial interactions in specific ecosystems. OrtSuite matched, on average, 96% of experimentally verified KEGG orthologs involved in benzoate degradation in a known group of benzoate degraders. We evaluated the identification of putative synergistic species interactions using the sequenced genomes of an independent study that had previously proposed potential species interactions in benzoate degradation. OrtSuite is an easy-to-use workflow that allows for rapid functional annotation based on a user-curated database and can easily be extended to ecosystem processes where connections between genes and reactions are known. OrtSuite is an open-source software available at https://github.com/mdsufz/OrtSuite.

Understanding the Gastrointestinal Protective Effects of Polyphenols using Foodomics-Based Approaches

Plant polyphenols are rich sources of natural anti-oxidants and prebiotics. After ingestion, most polyphenols are absorbed in the intestine and interact with the gut microbiota and modulated metabolites produced by bacterial fermentation, such as short-chain fatty acids (SCFAs). Dietary polyphenols immunomodulatory role by regulating intestinal microorganisms, inhibiting the etiology and pathogenesis of various diseases including colon cancer, colorectal cancer, inflammatory bowel disease (IBD) and colitis. Foodomics is a novel high-throughput analysis approach widely applied in food and nutrition studies, incorporating genomics, transcriptomics, proteomics, metabolomics, and integrating multi-omics technologies. In this review, we present an overview of foodomics technologies for identifying active polyphenol components from natural foods, as well as a summary of the gastrointestinal protective effects of polyphenols based on foodomics approaches. Furthermore, we critically assess the limitations in applying foodomics technologies to investigate the protective effect of polyphenols on the gastrointestinal (GI) system. Finally, we outline future directions of foodomics techniques to investigate GI protective effects of polyphenols. Foodomics based on the combination of several analytical platforms and data processing for genomics, transcriptomics, proteomics and metabolomics studies, provides abundant data and a more comprehensive understanding of the interactions between polyphenols and the GI tract at the molecular level. This contribution provides a basis for further exploring the protective mechanisms of polyphenols on the GI system.

HMGCS2 in metabolic pathways was associated with overall survival in hepatocellular carcinoma: A LASSO-derived study

This integrated bioinformatic study aimed to investigate potential prognostic candidates in hepatocellular carcinoma (HCC). In the GSE14520, GSE101685, and The Cancer Genome Atlas (TCGA) datasets, differentially expressed genes (DEGs) were identified and functional pathways of common DEGs were enriched. The least absolute shrinkage and selection operator (LASSO) model was used to screen the potential parameters associated with overall survival (OS) in HCC patients. Metabolic pathways were the most significantly enriched functional pathways of common DEGs in these three datasets. After LASSO model analysis, HMGCS2, UGP2, BCLC staging and TNM staging were screened as potential prognostic candidates for OS in HCC patients in GSE14520. HMGCS2 in the metabolic pathway was significantly downregulated in tumor tissues and peripheral blood mononuclear cells in HCC patients (all p < 0.05). Cox regression model indicated that HMGCS2 might be associate with OS in HCC patients in GSE14520 and in the TCGA (p = 0.029 and p = 0.05, respectively). Kaplan-Meier analysis demonstrated that HMGCS2 downregulation in tumors contributed to an unfavorable OS in HCC patients, both in GSE14520 and in the TCGA (p = 0.0001 and p = 0.0002, respectively). Additionally, HMGCS2 was significantly downregulated in HCC patients with high alpha-fetoprotein (AFP), main tumor size >5 cm, multinodular, advanced tumor staging including BCLC, TNM and CLIP (all p < 0.05). HMGCS2 was involved in metabolic pathways, and downregulated HMGCS2 in tumors was associated with unfavorable OS in HCC patients.

Dietary copper/zinc-loaded montmorillonite improved growth performance and intestinal barrier and changed gut microbiota in weaned piglets

The effects of copper/zinc-loaded montmorillonite (Cu/Zn-Mt) on growth performance, intestinal barrier and gut microbiota of weaned pigs were investigated in the present study. A total of 108 piglets (Duroc × Landrace × Yorkshire; 6.36 kg; weaned at 21 ± 1 d age) were used in this experiment. The pigs were randomly assigned to three treatments with six replicates, six pigs in each replicate. The three treatments were as follows: (1) control group: basal diet; (2) Cu/Zn-Mt group: basal diet supplemented with 39 mg/kg Cu and 75 mg/kg Zn as Cu/Zn-Mt; and (3) Cu +Zn +Mt group: basal diet supplemented with the mixture of copper sulphate, zinc sulphate and montmorillonite (equivalent to the copper and zinc in the Cu/Zn-Mt treatment). The results indicated that, compared with the pigs from control group, average daily gain and gain: feed ratio were increased and the faecal score on days 7 and 14 after weaning was decreased by supplementation of Cu/Zn-Mt; intestinal transepithelial electrical resistance (TER) and expressions of tight junction protein claudin-1 and zonula occludens-1 were increased, and intestinal permeability of fluorescein isothiocyanate-dextran 4 kDa was decreased by supplementation with Cu/Zn-Mt. According to the Illumina-based sequencing results, Cu/Zn-Mt supplementation increased the relative abundance of core bacteria (Lactococcus, Bacillus) at genus level and decreased the potentially pathogenic bacteria (Streptococcus and Pseudomonas) in colon of weaned piglets. However, the piglets fed with the mixture of copper sulphate, zinc sulphate and montmorillonite showed no effects in above parameters in comparison with the pigs from control group. In conclusion, dietary Cu/Zn-Mt could improve growth performance, decrease the diarrhoea and improve intestinal barrier and bacterial communities of weaned pigs. The results indicated that 'loading' of montmorillonite with Zn and Cu changed not only its chemical but also its nutritional properties.

MiR-330-3p and miR-485-5p as biomarkers for glioblastoma: An integrated bioinformatics and experimental study

Glioblastoma Multiforme (GBM) is the most common, invasive, and malignant primary brain tumor with a poor prognosis and a median survival of 12-15 months. This study tried to identify the most significant miRNA biomarkers in both tissue and serum samples of GBM. GSE25632 was employed from gene expression omnibus and using WGCNA package, association of miRNA networks and clinical data was explored and brown and green modules identified as the most relevant modules. Independently, Limma package was utilized to identify differentially expressed miRNAs (DEMs) in GSE25632 by cutoff logFC > 2 and P.value < 0.05. By merging the results of Limma and WGCNA, the miRNAs that were in brown and green modules and had mentioned cutoff were selected as hub miRNAs. Performing enrichment analysis, Pathways in cancer, Prostate cancer, Glioma, p53 signaling pathway, and Focal adhesion were identified as the most important signaling pathways. Based on miRNA- target genes, has-mir-330-3p and has-mir-485-5p were identified as core miRNAs. The expression level of core miRNAs was validated by GSE90604, GSE42657, and GSE93850. We evaluated the expression level of common target genes of two detected core genes based on GSE77043, GSE42656, GSE22891, GSE15824, and GSE122498. The ability of detected miRNAs to discriminate GBM from healthy controls was assessed by area under the curve (AUC) using the ROC curve analysis. Based on TCGA database, we tested the prognostic significance of miRNAs using overall survival analysis. We evaluated the expression level of the miRNAs in tissue of 83 GBM patients and also non-tumoral adjacent (as control) tissues. We used serum samples of 34 GBM patients to evaluate the expression levels of the hub miRNAs compare to the controls. Our results showed that has-mir-330-3p and has-mir-485-5p could be potential biomarkers in GBM.

Recent Advanced Technologies for the Characterization of Xenobiotic-Degrading Microorganisms and Microbial Communities

Global environmental contamination with a complex mixture of xenobiotics has become a major environmental issue worldwide. Many xenobiotic compounds severely impact the environment due to their high toxicity, prolonged persistence, and limited biodegradability. Microbial-assisted degradation of xenobiotic compounds is considered to be the most effective and beneficial approach. Microorganisms have remarkable catabolic potential, with genes, enzymes, and degradation pathways implicated in the process of biodegradation. A number of microbes, including Alcaligenes, Cellulosimicrobium, Microbacterium, Micrococcus, Methanospirillum, Aeromonas, Sphingobium, Flavobacterium, Rhodococcus, Aspergillus, Penecillium, Trichoderma, Streptomyces, Rhodotorula, Candida, and Aureobasidium, have been isolated and characterized, and have shown exceptional biodegradation potential for a variety of xenobiotic contaminants from soil/water environments. Microorganisms potentially utilize xenobiotic contaminants as carbon or nitrogen sources to sustain their growth and metabolic activities. Diverse microbial populations survive in harsh contaminated environments, exhibiting a significant biodegradation potential to degrade and transform pollutants. However, the study of such microbial populations requires a more advanced and multifaceted approach. Currently, multiple advanced approaches, including metagenomics, proteomics, transcriptomics, and metabolomics, are successfully employed for the characterization of pollutant-degrading microorganisms, their metabolic machinery, novel proteins, and catabolic genes involved in the degradation process. These technologies are highly sophisticated, and efficient for obtaining information about the genetic diversity and community structures of microorganisms. Advanced molecular technologies used for the characterization of complex microbial communities give an in-depth understanding of their structural and functional aspects, and help to resolve issues related to the biodegradation potential of microorganisms. This review article discusses the biodegradation potential of microorganisms and provides insights into recent advances and omics approaches employed for the specific characterization of xenobiotic-degrading microorganisms from contaminated environments.

Involvement of Differentially Expressed microRNAs in the PEGylated Liposome Encapsulated 188Rhenium-Mediated Suppression of Orthotopic Hypopharyngeal Tumor

Hypopharyngeal cancer (HPC) accounts for the lowest survival rate among all types of head and neck cancers (HNSCC). However, the therapeutic approach for HPC still needs to be investigated. In this study, a theranostic ¹⁸⁸Re-liposome was prepared to treat orthotopic HPC tumors and analyze the deregulated microRNA expressive profiles. The therapeutic efficacy of ¹⁸⁸Re-liposome on HPC tumors was evaluated using bioluminescent imaging followed by next generation sequencing (NGS) analysis, in order to address the deregulated microRNAs and associated signaling pathways. The differentially expressed microRNAs were also confirmed using clinical HNSCC samples and clinical information from The Cancer Genome Atlas (TCGA) database. Repeated doses of ¹⁸⁸Re-liposome were administrated to tumor-bearing mice, and the tumor growth was apparently suppressed after treatment. For NGS analysis, 13 and 9 microRNAs were respectively up-regulated and down-regulated when the cutoffs of fold change were set to 5. Additionally, miR-206-3p and miR-142-5p represented the highest fold of up-regulation and down-regulation by ¹⁸⁸Re-liposome, respectively. According to Differentially Expressed MiRNAs in human Cancers (dbDEMC) analysis, most of ¹⁸⁸Re-liposome up-regulated microRNAs were categorized as tumor suppressors, while down-regulated microRNAs were oncogenic. The KEGG pathway analysis showed that cancer-related pathways and olfactory and taste transduction accounted for the top pathways affected by ¹⁸⁸Re-liposome. ¹⁸⁸Re-liposome down-regulated microRNAs, including miR-143, miR-6723, miR-944, and miR-136 were associated with lower survival rates at a high expressive level. ¹⁸⁸Re-liposome could suppress the HPC tumors in vivo, and the therapeutic efficacy was associated with the deregulation of microRNAs that could be considered as a prognostic factor.

Species-specific genomic sequences for classification of bacteria

Modern bacterial classification relies on genomic relatedness. Genetic variation in bacterial populations present a big challenge for taxonomic classification and recently several bacterial species have been reclassified based on the intra-species genome comparison. These were facilitated by next generation sequencing technologies and advances in genome comparison approaches which led to the rearrangement of diverse bacterial species and revolution in the microbial classification system. One of the outcome of these studies is the development of suitable DNA barcodes as reliable and cost-effective method for identifying various bacterial genera. Towards refining this further, we have applied a genome comparison approach in 1104 bacterial genome assemblies (excluding plasmids) to identify unique genomic segments among intra-species genome assemblies. Using extensive bioinformatics analysis, we have identified species-specific genomic regions and designed unique primers for 100 different species (belonging to 62 genera) which includes 62 pathogenic and 13 opportunistic pathogenic bacterial species and built a database (http://slsdb.manipal.edu/bact/). These species-specific genomic regions will have a major impact on in silico and molecular methods aimed at bacterial classification and identification. These may also serve as better DNA barcodes than the markers currently used for delineation of bacteria and may also find application in various translational research programs.

Potential for co-metabolic oxidation of TCE and evidence for its occurrence in a large-scale aquifer survey

Trichloroethylene (TCE) is a groundwater pollutant that is prevalent worldwide. In contaminated groundwater, TCE can be biodegraded following either reductive dechlorination or aerobic co-metabolic oxidation. However, since the co-metabolic process is not accompanied by indicative and easily detectable transformation products, little is known about its prominence in the environment. To estimate the environmental importance of the oxidative process, a regional groundwater survey was conducted. In this survey, polluted water from 100 wells along the Israeli Coastal Aquifer was sampled. Geochemical data indicated oxic conditions prevailing in most sites. The sampled groundwater was used for microcosm experiments, functional gene analysis, and TCE compound-specific isotope analysis (δ¹³C and δ³⁷Cl). Enrichments of methane and toluene oxidizers in microcosms indicated the high potential of the indigenous microbial community to co-metabolically oxidize TCE. This was further reinforced by the high abundance of mmoX and PHE functional genes quantified in some of the sites (yet lower abundance of TOD functional gene was found). Finally, compound-specific isotope analysis was used to assess the magnitude of TCE oxidation in practice. Applying the isotopic tool for scattered points on a regional scale demanded the consideration of a wide δ¹³C range of source TCE, hampering the ability to detect small shifts of a single permil. Thus, despite the high potential for the oxidation process, no evidence was attained for the natural occurrence of the process, and significant isotopic shifts were restricted to actively treated sites only. This limitation should be considered in future regional scale studies, in which no single source is defined.

Technological Advances in Phytopathogen Detection and Metagenome Profiling Techniques

The use of advanced molecular methods in plant pathology and applied microbiology has necessitated for more accurate, rapid detection and identification of plant pathogens. This is particularly significant given accelerated emergence of virulence that leads to increased prevalence of plant pathogens. Thus, the capacity to contain plant pathogens and ultimately disease progression is key to ensuring crop biosecurity and overall food security. Of recent, research on pathogens utilizes a holistic approach focusing on elucidating growth dynamics within the entire biome rather than studying individual or closely related isolates in unison. This has advanced knowledge and information of microbial ecosystem within natural environments in the twenty first century. Applied technological platforms used for rapid detection and profiling microbial biomes in this regard include digital PCR, pyrosequencing, Illumina, DNA microarray and barcoding, Ion torrent, and nanopore. These technologies have been applied in various fields including human health and medicine, marine and animal biology, crop production and water quality research, to mention but a few. Although much has been done and achieved through the development of several technologies, more accuracy is required to circumvent the shortfalls still experienced. This includes integrating existing methods with new applications such as viability PCRs and microbial viability testing. Hence, this review provides critical analysis of some widely used latest technologies in rapid detection and identification of plant pathogens, and profiling plant associated microbiomes that reveal growth dynamics and population diversity. The advantages and limitations of the technologies are also discussed.

Arsenic mobilization in a high arsenic groundwater revealed by metagenomic and Geochip analyses

Microbial metabolisms of arsenic, iron, sulfur, nitrogen and organic matter play important roles in arsenic mobilization in aquifer. In this study, microbial community composition and functional potentials in a high arsenic groundwater were investigated using integrated techniques of RNA- and DNA-based 16S rRNA gene sequencing, metagenomic sequencing and functional gene arrays. 16S rRNA gene sequencing showed the sample was dominated by members of Proteobacteria (62.3-75.2%), such as genera of Simplicispira (5.7-6.7%), Pseudomonas (3.3-5.7%), Ferribacterium (1.6-4.4%), Solimonas (1.8-3.2%), Geobacter (0.8-2.2%) and Sediminibacterium (0.6-2.4%). Functional potential analyses indicated that organics degradation, assimilatory sulfate reduction, As-resistant pathway, iron reduction, ammonification, nitrogen fixation, denitrification and dissimilatory nitrate reduction to ammonia were prevalent. The composition and function of microbial community and reconstructed genome bins suggest that high level of arsenite in the groundwater may be attributed to arsenate release from iron oxides reductive dissolution by the iron-reducing bacteria, and subsequent arsenate reduction by ammonia-producing bacteria featuring ars operon. This study highlights the relationship between biogeochemical cycling of arsenic and nitrogen in groundwater, which potentially occur in other aquifers with high levels of ammonia and arsenic.

Identification of significant gene and pathways involved in HBV-related hepatocellular carcinoma by bioinformatics analysis

Background

Hepatocellular carcinoma (HCC) is a common malignant tumor affecting the digestive system and causes serious financial burden worldwide. Hepatitis B virus (HBV) is the main causative agent of HCC in China. The present study aimed to investigate the potential mechanisms underlying HBV-related HCC and to identify core biomarkers by integrated bioinformatics analyses.

Methods

In the present study, HBV-related HCC GSE19665, GSE55092, GSE94660 and GSE121248 expression profiles were downloaded from the Gene Expression Omnibus database. These databases contain data for 299 samples, including 145 HBV-related HCC tissues and 154 non-cancerous tissues (from patients with chronic hepatitis B). The differentially expressed genes (DEGs) from each dataset were integrated and analyzed using the RobustRankAggreg (RRA) method and R software, and the integrated DEGs were identified. Subsequently, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the DAVID online tool, and the protein-protein interaction (PPI) network was constructed using STRING and visualized using Cytoscape software. Finally, hub genes were identified, and the cBioPortal online platform was used to analyze the association between the expression of hub genes and prognosis in HCC.

Results

First, 341 DEGs (117 upregulated and 224 downregulated) were identified from the four datasets. Next, GO analysis showed that the upregulated genes were mainly involved in cell cycle, mitotic spindle, and adenosine triphosphate binding. The majority of the downregulated genes were involved in oxidation reduction, extracellular region, and electron carrier activity. Signaling pathway analysis showed that the integrated DEGs shared common pathways in retinol metabolism, drug metabolism, tryptophan metabolism, caffeine metabolism, and metabolism of xenobiotics by cytochrome P450. The integrated DEG PPI network complex comprised 288 nodes, and two important modules with high degree were detected using the MCODE plug-in. The top ten hub genes identified from the PPI network were SHCBP1, FOXM1, KIF4A, ANLN, KIF15, KIF18A, FANCI, NEK2, ECT2, and RAD51AP1. Finally, survival analysis revealed that patients with HCC showing altered ANLN and KIF18A expression profiles showed worse disease-free survival. Nonetheless, patients with FOXM1, NEK2, RAD51AP1, ANLN, and KIF18A alterations showed worse overall survival.

Conclusions

The present study identified key genes and pathways involved in HBV-related HCC, which improved our understanding of the mechanisms underlying the development and recurrence of HCC and identified candidate targets for the diagnosis and treatment of HBV-related HCC.

Mycobiome Diversity in Traditionally Prepared Starters for Alcoholic Beverages in India by High-Throughput Sequencing Method

Chowan, dawdim, humao, hamei, khekhrii, and phut are sun-dried starters used for preparation of alcoholic beverages in North East regions of India. We attempted to profile the mycobiome community in these starters by high-throughput sequencing (HTS) method. All fungal populations were found to be restricted to Ascomycota (67-99%), Zygomycota (0.7-29%), Basidiomycota (0.03-7%), and Chytridiomycota (0.0003%). We found 45 core operational taxonomic units (OTUs) which were universally present and were further weighed to 41 genera level and 22 species level taxonomy. A total number of 594 fungal species were detected by HTS including common species (224), unique species (133) and rare-species (237) in samples of starters. Unique species were recorded in phut (40 species), khekhrii (28), hamei (23), dawdim (21), chowan (13), and humao (8), respectively. Most of the fungal families were found to correlate to a type of nutritional mode and growth morphologies of the community, where saprotrophic mode of mold species were more dominant, whereas morphotypes were more dominant in yeast species.

Genome-wide expression profiling of glioblastoma using a large combined cohort

Glioblastomas (GBMs), are the most common intrinsic brain tumors in adults and are almost universally fatal. Despite the progresses made in surgery, chemotherapy, and radiation over the past decades, the prognosis of patients with GBM remained poor and the average survival time of patients suffering from GBM was still short. Discovering robust gene signatures toward better understanding of the complex molecular mechanisms leading to GBM is an important prerequisite to the identification of novel and more effective therapeutic strategies. Herein, a comprehensive study of genome-scale mRNA expression data by combining GBM and normal tissue samples from 48 studies was performed. The 147 robust gene signatures were identified to be significantly differential expression between GBM and normal samples, among which 100 (68%) genes were reported to be closely associated with GBM in previous publications. Moreover, function annotation analysis based on these 147 robust DEGs showed certain deregulated gene expression programs (e.g., cell cycle, immune response and p53 signaling pathway) were associated with GBM development, and PPI network analysis revealed three novel hub genes (RFC4, ZWINT and TYMS) play important role in GBM development. Furthermore, survival analysis based on the TCGA GBM data demonstrated 38 robust DEGs significantly affect the prognosis of GBM in OS (p < 0.05). These findings provided new insights into molecular mechanisms underlying GBM and suggested the 38 robust DEGs could be potential targets for the diagnosis and treatment.

Proteomics and the microbiome: pitfalls and potential

Introduction: Human symbiotic microbiota are now known to play important roles in human health and disease. Significant progress in our understanding of the human microbiome has been driven by recent technological advances in the fields of genomics, transcriptomics, and proteomics. As a complementary method to metagenomics, proteomics is enabling detailed protein profiling of the microbiome to decipher its structure and function and to analyze its relationship with the human body. Fecal proteomics is being increasingly applied to discover and validate potential health and disease biomarkers, and Therapeutic Goods Administration (TGA)-approved instrumentation and a range of clinical assays are being developed that will collectively play key roles in advancing personalized medicine. Areas covered: This review will introduce the complexity of the microbiome and its role in health and disease (in particular the gastrointestinal tract or gut microbiome), discuss current genomic and proteomic methods for studying this system, including the discovery of potential biomarkers, and outline the development of clinically accepted protocols leading to personalized medicine. Expert commentary: Recognition of the important role the microbiome plays in both health and disease is driving current research in this key area. A proteogenomics approach will be essential to unravel the biologies underlying this complex network.

Barcoded Pyrosequencing Reveals a Shift in the Bacterial Community in the Rhizosphere and Rhizoplane of Rehmannia glutinosa under Consecutive Monoculture

The production and quality of Rehmannia glutinosa can be dramatically reduced by replant disease under consecutive monoculture. The root-associated microbiome, also known as the second genome of the plant, was investigated to understand its impact on plant health. Culture-dependent and culture-independent pyrosequencing analysis was applied to assess the shifts in soil bacterial communities in the rhizosphere and rhizoplane under consecutive monoculture. The results show that the root-associated microbiome (including rhizosphere and rhizoplane microbiomes) was significantly impacted by rhizocompartments and consecutive monoculture. Consecutive monoculture of R. glutinosa led to a significant decline in the relative abundance of the phyla Firmicutes and Actinobacteria in the rhizosphere and rhizoplane. Furthermore, the families Flavobacteriaceae, Sphingomonadaceae, and Xanthomonadaceae enriched while Pseudomonadaceae, Bacillaceae, and Micrococcaceae decreased under consecutive monoculture. At the genus level, Pseudomonas, Bacillus, and Arthrobacter were prevalent in the newly planted soil, which decreased in consecutive monocultured soils. Besides, culture-dependent analysis confirmed the widespread presence of Pseudomonas spp. and Bacillus spp. in newly planted soil and their strong antagonistic activities against fungal pathogens. In conclusion, R. glutinosa monoculture resulted in distinct root-associated microbiome variation with a reduction in the abundance of beneficial microbes, which might contribute to the declined soil suppressiveness to fungal pathogens in the monoculture regime.

A comparative study of composting the solid fraction of dairy manure with or without bulking material: Performance and microbial community dynamics

The present study compared the development of various physicochemical properties and the composition of microbial communities involved in the composting process in the solid fraction of dairy manure (SFDM) with a sawdust-regulated SFDM (RDM). The changes in several primary physicochemical properties were similar in the two composting processes, and both resulted in mature end-products within 48days. The bacterial communities in both composting processes primarily comprised Proteobacteria and Bacteroidetes. Firmicutes were predominant in the thermophilic phase, whereas Chloroflexi, Planctomycetes, and Nitrospirae were more abundant in the final mature phase. Furthermore, the succession of bacteria in both groups proceeded in a similar pattern, suggesting that the effects of the bulking material on bacterial dynamics were minor. These results demonstrate the feasibility of composting using only the SFDM, reflected by the evolution of physicochemical properties and the microbial communities involved in the composting process.

Transcriptomic profiling of taproot growth and sucrose accumulation in sugar beet (Beta vulgaris L.) at different developmental stages

In sugar beet (Beta vulgaris L.), taproot weight and sucrose content are the important determinants of yield and quality. However, high yield and low sucrose content are two tightly bound agronomic traits. The advances in next-generation sequencing technology and the publication of sugar beet genome have provided a method for the study of molecular mechanism underlying the regulation of these two agronomic traits. In this work, we performed comparative transcriptomic analyses in the high taproot yield cultivar SD13829 and the high sucrose content cultivar BS02 at five developmental stages. More than 50,000,000 pair-end clean reads for each library were generated. When taproot turned into the rapid growth stage at the growth stage of 82 days after emergence (DAE), eighteen enriched gene ontology (GO) terms, including cell wall, cytoskeleton, and enzyme linked receptor protein signaling pathway, occurred in both cultivars. Differentially expressed genes (DEGs) of paired comparison in both cultivars were enriched in the cell wall GO term. For pathway enrichment analyses of DEGs that were respectively generated at 82 DAE compared to 59 DAE (the earlier developmental stage before taproot turning into the rapid growth stage), plant hormone signal transduction pathway was enriched. At 82 DAE, the rapid enlarging stage of taproot, several transcription factor family members were up-regulated in both cultivars. An antagonistic expression of brassinosteroid- and auxin-related genes was also detected. In SD13829, the growth strategy was relatively focused on cell enlargement promoted by brassinosteroid signaling, whereas in BS02, it was relatively focused on secondarily cambial cell division regulated by cytokinin, auxin and brassinosteroid signaling. Taken together, our data demonstrate that the weight and sucrose content of taproot rely on its growth strategy, which is controlled by brassinosteroid, auxin, cytokinin, and gibberellin.

Intestinal microbiome landscaping: insight in community assemblage and implications for microbial modulation strategies

High individuality, large complexity and limited understanding of the mechanisms underlying human intestinal microbiome function remain the major challenges for designing beneficial modulation strategies. Exemplified by the analysis of intestinal bacteria in a thousand Western adults, we discuss key concepts of the human intestinal microbiome landscape, i.e. the compositional and functional 'core', the presence of community types and the existence of alternative stable states. Genomic investigation of core taxa revealed functional redundancy, which is expected to stabilize the ecosystem, as well as taxa with specialized functions that have the potential to shape the microbiome landscape. The contrast between Prevotella- and Bacteroides-dominated systems has been well described. However, less known is the effect of not so abundant bacteria, for example, Dialister spp. that have been proposed to exhibit distinct bistable dynamics. Studies employing time-series analysis have highlighted the dynamical variation in the microbiome landscape with and without the effect of defined perturbations, such as the use of antibiotics or dietary changes. We incorporate ecosystem-level observations of the human intestinal microbiota and its keystone species to suggest avenues for designing microbiome modulation strategies to improve host health.

An improved protocol with a highly degenerate primer targeting copper-containing membrane-bound monooxygenase genes for community analysis of methane- and ammonia-oxidizing bacteria

The copper-containing membrane-bound monooxygenase (CuMMO) family comprises key enzymes for methane or ammonia oxidation: particulate methane monooxygenase (PMMO) and ammonia monooxygenase (AMO). To comprehensively amplify CuMMO genes, a two-step PCR strategy was developed using a newly designed tagged highly degenerate primer (THDP; degeneracy = 4608). Designated THDP-PCR, the technique consists of primary CuMMO gene-specific PCR followed by secondary PCR with a tag as a single primer. No significant bias in THDP-PCR amplification was found using various combinations of template mixtures of pmoA and amoA genes, which encode key subunits of the pMMO and AMO enzymes, respectively, from different microbes. THDP-PCR was successfully applied to nine different environmental samples and revealed relatively high contents of complete ammonia oxidation (Comammox)-related bacteria and a novel group of the CuMMO family. The levels of freshwater cluster methanotrophs obtained by THDP-PCR were much higher than those obtained by conventional methanotroph-specific PCR. The THDP-PCR strategy developed in this study can be extended to other functional gene-based community analyses, particularly when the target gene sequences lack regions of high consensus for primer design.

Studying the Human Microbiota

There are a range of methodologies available to study the human microbiota, ranging from traditional approaches such as culturing through to state-of-the-art developments in next generation DNA sequencing technologies. The advent of molecular techniques in particular has opened up tremendous new avenues for research, and has galvanised interest in the study of our microbial inhabitants. Given the dazzling array of available options, however, it is important to understand the inherent advantages and limitations of each technique so that the best approach can be employed to address the particular research objective. In this chapter we cover some of the most widely used current techniques in human microbiota research and highlight the particular strengths and caveats associated with each approach.

Characterization of microbial communities in wetland mesocosms receiving caffeine-enriched wastewater

A 454 high-throughput pyrosequencing approach was used to characterize the structures of microbial communities in wetland mesocosms receiving caffeine-enriched wastewater at a concentration of 250 μg L(-1). The removal efficiencies of caffeine in the planted beds (93.0 %) were significantly (p < 0.05) higher than those in the unplanted beds (81.4 %). Bacterial diversity was decreased by 25 and 22.4 %, respectively, in both planted and unplanted mesocosms after 210-day operation. The results of taxonomic analyses suggested that chronic exposure of wetland ecosystems to caffeine could lead to moderate shifts in microbial community composition. In total, 2156 operational taxonomic units (OTUs) were generated and 20 phyla comprising 260 genera were identified. The major phylogenetic groups at phylum level included Firmicutes (39 %), Actinobacteria (25.1 %), Proteobacteria (17.1 %), Synergistetes (5.6 %), and Chloroflexi (5.5 %). Bacilli and Synergistia increased in abundance in the planted mesocosms, while for the unplanted mesocosms, Actinobacterial, Clostridia and Betaproteobacteria exhibited increased proportion under the exposure of caffeine. At genus level, Propionibacterium, Staphylococcus, Bacillus, and Streptococcus were found to be increased in abundance after caffeine treatment. As for the response of fungal community to caffeine enrichment, genus like Cladosporium, Emericellopsis, Aspergillus, and Phoma were found to be resistant to caffeine disturbance. When compared to the microbial community between planted and unplanted mesocosms, a distinct community profile for both bacteria and fungi community was observed. The presence of plants had a remarkable effect on the structure of microbial community, helping buffer against the stress associated with caffeine exposure.

Illumina MiSeq sequencing reveals long-term impacts of single-walled carbon nanotubes on microbial communities of wastewater treatment systems

In this study, phenol wastewater treatment systems treated with different concentrations of single-walled carbon nanotubes (SWCNTs) (0-3.5g/L) were exposed to phenol and carbon nanotubes (CNTs) shock loadings to investigate the long-term impacts of SWCNTs on microbial communities. Phenol removal remained high efficiency (>98%) in SWCNTs-treated groups but decreased in non-treated group (85.1±1.9%) when exposed to high concentration of phenol (500mg/L). However, secondary dosing of SWCNTs in SWCNTs-treated groups would decrease the phenol removal efficiency. Illumina MiSeq sequencing revealed that the diversity, richness and structure of microbial communities were shifted under phenol shock loading, especially under high phenol concentration, but not under CNTs shock loading. In response to phenol and CNTs shock loadings, Rudaea, Burkholderia, Sphingomonas, Acinetobacter, Methylocystis and Thauera became dominant genera, which should be involved in phenol removal. These results suggested that a proper amount of SWCNTs might have positive effects on phenol wastewater treatment systems.

Molecular assessment of bacterial vaginosis by Lactobacillus abundance and species diversity

Background

To date, women are most often diagnosed with bacterial vaginosis (BV) using microscopy based Nugent scoring or Amsel criteria. However, the accuracy is less than optimal. The aim of the present study was to confirm the identity of known BV-associated composition profiles and evaluate indicators for BV using three molecular methods.

Methods

Evaluation of indicators for BV was carried out by 16S rRNA amplicon sequencing of the V5-V7 region, a tailor-made 16S rRNA oligonucleotide-based microarray, and a PCR-based profiling technique termed IS-profiling, which is based on fragment variability of the 16S-23S rRNA intergenic spacer region. An inventory of vaginal bacterial species was obtained from 40 females attending a Dutch sexually transmitted infection outpatient clinic, of which 20 diagnosed with BV (Nugent score 7–10), and 20 BV negative (Nugent score 0–3).

Results

Analysis of the bacterial communities by 16S rRNA amplicon sequencing revealed two clusters in the BV negative women, dominated by either Lactobacillus iners or Lactobacillus crispatus and three distinct clusters in the BV positive women. In the former, there was a virtually complete, negative correlation between L. crispatus and L. iners. BV positive subjects showed cluster profiles that were relatively high in bacterial species diversity and dominated by anaerobic species, including Gardnerella vaginalis, and those belonging to the Families of Lachnospiraceae and Leptotrichiaceae. Accordingly, the Gini-Simpson index of species diversity, and the relative abundance Lactobacillus species appeared consistent indicators for BV. Under the conditions used, only the 16S rRNA amplicon sequencing method was suitable to assess species diversity, while all three molecular composition profiling methods were able to indicate Lactobacillus abundance in the vaginal microbiota.

Conclusion

An affordable and simple molecular test showing a depletion of the genus Lactobacillus in combination with an increased species diversity of vaginal microbiota could serve as an alternative and practical diagnostic method for the assessment of BV.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-016-1513-3) contains supplementary material, which is available to authorized users.

Development and validation of a custom microarray for global transcriptome profiling of the fungus Aspergillus nidulans

Transcriptome profiling is a powerful tool for identifying gene networks from whole genome expression analysis in many living species. Here is described the first extensively characterized platform using Agilent microarray technology for transcriptome analysis in the filamentous fungus Aspergillus (Emericella) nidulans. We developed and validated a reliable gene expression microarray in 8 × 15 K format, with predictive and experimental data establishing its specificity and sensitivity. Either one or two 60-mer oligonucleotide probes were selected for each of 10,550 nuclear as well as 20 mitochondrial coding sequences. More than 99 % of probes were predicted to hybridize with 100 % identity to their aimed specific A. nidulans target only. Probe sensitivity was supported by a highly narrow distribution of melting temperatures together with thermodynamic features, which strongly favored probe-target perfect match hybridization, in comparison with predicted secondary structures. Array quality was evaluated through transcriptome comparison of two A. nidulans strains, differing by the presence or not of Escherichia coli LacZ transgene. High signal-to-noise ratios were measured, and signal reproducibility was established at intra-probe and inter-probe levels. Reproducibility of microarray performances was assessed by high correlation between two-color dye signals and between technical replicates. Results were confirmed by RT-qPCR analysis on five genes. Though it covers 100 % of the A. nidulans targeted coding sequences, this low density array allows limited experimental costs and simplified data analysis process, making it suitable for studying gene expression in this model organism through large numbers of experimental conditions, in basic, biomedical or industrial microbiology research fields.

Metagenomic exploration of the bacterial community structure at Paradip Port, Odisha, India

This is a pioneering report on the metagenomic exploration of the bacterial diversity from a busy sea port in Paradip, Odisha, India. In our study, high-throughput sequencing of community 16S rRNA gene amplicon was performed using 454 GS Junior platform. Metagenome contain 34,121 sequences with 16,677,333 bp and 56.3% G + C content. Metagenome sequences data are now available at NCBI under the Sequence Read Archive (SRA) database with accession no. SRX897055. Community metagenome sequence revealed the presence of 11,705 species belonging to 40 different phyla. Bacteroidetes (23%), Firmicutes (19%), Proteobacteria (17%), Spirochaetes (10%), Nitrospirae (8%), Actinobacteria (7%) and Acidobacteria (3%) are the predominant bacterial phyla in this port soil. Analysis of metagenomic sequences unfolded the interesting distribution of several phyla which pointed to the significant anthropogenic intervention influencing the bacterial community character of this port.

Antibiotic resistance genes and human bacterial pathogens: Co-occurrence, removal, and enrichment in municipal sewage sludge digesters

Understanding which/how antibiotic resistance genes (ARGs) contribute to increased acquisition of resistance by pathogens in aquatic environments are challenges of profound significance. We explored the co-occurrence and removal versus enrichment of ARGs and human bacterial pathogens (HBPs) in municipal sewage sludge digesters. We combined metagenomic detection of a wide spectrum of 323 ARGs and 83 HBPs with a correlation-based statistical approach and charted a network of their co-occurrence relationships. The results indicate that most ARGs and a minor proportion of HBPs (mainly Collinsella aerofaciens, Streptococcus salivarius and Gordonia bronchialis) could not be removed by anaerobic digestion, revealing a biological risk of post-digestion sludge in disseminating antibiotic resistance and pathogenicity. Moreover, preferential co-occurrence patterns were evident within one ARG type (e.g., multidrug, beta-lactam, and aminoglycoside) and between two different ARG types (i.e., aminoglycoside and beta-lactam), possibly implicating co-effects of antibiotic selection pressure and co-resistance on shaping antibiotic resistome in sewage sludge. Unlike beta-lactam resistance genes, ARGs of multidrug and macrolide-lincosamide-streptogramin tended to co-occur more with HBPs. Strikingly, we presented evidence that the most straightforward biological origin of an ARG-species co-occurring event is a hosting relationship. Furthermore, a significant and robust HBP-species co-occurrence correlation provides a proper scenario for nominating HBP indicators (e.g., Bifidobacterium spp. are perfect indicators of C. aerofaciens; r = 0.92-0.99 and P-values < 0.01). Combined, this study demonstrates a creative and effective network-based metagenomic approach for exploring ARG hosts and HBP indicators and assessing ARGs acquisition by HBPs in human-impacted environments where ARGs and HBPs may co-thrive.

A new perspective on microbial landscapes within food production

High-throughput, 'next-generation' sequencing tools offer many exciting new possibilities for food research. From investigating microbial dynamics within food fermentations to the ecosystem of the food-processing built environment, amplicon sequencing, metagenomics, and transcriptomics present novel applications for exploring microbial communities in, on, and around our foods. This review discusses the many uses of these tools for food-related and food facility-related research and highlights where they may yield nuanced insight into the microbial world of food production systems.

Ibuprofen removal in horizontal subsurface flow constructed wetlands: treatment performance and fungal community dynamics

The treatment performance of ibuprofen (IBP)-enriched wastewater by horizontal subsurface flow constructed wetlands planted with cattail (Typha angustifolia) and unplanted control mesocosms was investigated. Removal efficiencies of IBP were significantly (p < .05) enhanced in the planted mesocosms (78.5%) compared to those in the unplanted beds (57.9%). An 18S rRNA gene high-throughput pyrosequencing approach was used to investigate the effects of IBP on the structure of the fungal community in these wetland systems. The overall diversity of the fungal community was reduced under the IBP exposure. Taxonomic analysis revealed that 62.2% of the fungal sequences were affiliated with Basidiomycota, followed by Ascomycota (37.4%) at the phylum level. Uncultured fungus (48.2%), Chaetomium sp. (14.2%), Aspergillus sp. (12.4%), Trichoderma sp. (5.7%), Cladosporium sp. (5.4%), and Emericellopsis sp. (5.2%) were identified as dominant genera. At the genus level, a distinct profile of the fungal community in the IBP-enriched mesocosms was observed as compared to the control beds, and as well specific fungal genera were enhanced in the planted beds, regardless of IBP enrichment. However, despite these differences, the composition of the fungal community (as measured by Bray-Curtis similarity) was mostly unaffected by the significant IBP enrichment. On the other hand, a consistent similarity pattern of fungal community structure in the planted mesocosms suggests that the presence of higher macrophytes in the wetland systems may well help shape the fungal community structure.

Characterizing the Intestinal Microbiome in Infantile Colic: Findings Based on an Integrative Review of the Literature

Approximately 20% of newborns will develop symptoms of infantile colic starting around 2 weeks of age. While health care providers have a greater understanding of the impact that inconsolable crying has on family dynamics, maternal-infant bonding, and health care resources, opportunities for study still exist in the area of intestinal microbiome research. Advances in molecular technologies utilizing 16S ribosomal RNA and ribosomal DNA created the opportunity for researchers to index the intestinal microbial composition to better understand its association with infantile colic. This integrative review provides a synopsis of the findings from five recent studies that utilized nonculture-based approaches to characterize the intestinal microbiome of infants with colic. Articles were identified through PubMed, CINAHL, and Google Scholar using the search terms colic, crying, fussiness, microbiome, and microbiota. The general aim of the research studies was to better understand the potential association of intestinal dysbiosis with the development of colic symptoms. The research found that infants who expressed symptoms of colic were colonized with significantly higher levels of Proteobacteria and exhibited lower bacterial diversity when compared to their unaffected counterparts. Additionally, colonization levels of Actinobacteria Bifidobacterium and Firmicute Lactobacilli were inversely related to the amount of crying and fussiness in newborns. The observed association of an imbalanced colonization of the intestines by noncommensal bacteria with the expression of infantile colic symptoms warrants further exploration.