Application of 'next-generation' sequencing technologies to microbial genetics

A preliminary study of gene expression changes in Koalas Infected with Koala Retrovirus (KoRV) and identification of potential biomarkers for KoRV pathogenesis

BACKGROUND

Koala retrovirus (KoRV), a major pathogen of koalas, exists in both endogenous (KoRV-A) and exogenous forms (KoRV-A to I and K to M) and causes multiple disease phenotypes, including carcinomas and immunosuppression. However, the direct association between the different KoRV subtypes and carcinogenesis remains unknown. Differentially expressed gene (DEG) analysis of peripheral blood mononuclear cells (PBMCs) of koalas carrying both endogenous (KoRV-A) and exogenous (KoRV-A, B, and C) subtypes was performed using a high-throughput RNA-seq approach. PBMCs were obtained from three healthy koalas: one infected with endogenous (KoRV-A; Group I) and two infected with exogenous (KoRV-B and/or KoRV-C; Group II) subtypes. Additionally, spleen samples (n = 6) from six KoRV-infected deceased koalas (K1- K6) and blood samples (n = 1) from a live koala (K7) were collected and examined to validate the findings.

RESULTS

All koalas were positive for the endogenous KoRV-A subtype, and eight koalas were positive for KoRV-B and/or KoRV-C. Transcription of KoRV gag, pol, and env genes was detected in all koalas. Upregulation of cytokine and immunosuppressive genes was observed in koalas infected with KoRV-B or KoRV-B and -C subtypes, compared to koalas infected with only KoRV-A. We found 550 DEG signatures with significant (absolute p < 0.05, and absolute log2 Fold Change (FC) > 1.5) dysregulation, out of which 77.6% and 22.4% DEGs were upregulated (log2FC > 1.5) and downregulated (log2FC <  - 1.5), and downregulated (log2 FC <  - 1), respectively. We identified 17 unique hub genes (82.3% upregulated and 17.7% down-regulated), with KIF23, CCNB2, POLR3F, and RSL24D1 detected as the potential hub genes modified with KoRV infection. Real-time RT-qPCR was performed on seven koalas to ascertain the expression levels of four potential hub genes, which were subsequently normalized to actin copies. Notably, all seven koalas exhibited distinct expression signatures for the hub genes, especially, KIF23 and CCNB2 show the highest expression in healthy koala PBMC, and POLR3F shows the highest expression in koala with lymphoma (K1).

CONCLUSION

Thus, it can be concluded that multiple KoRV subtypes affect disease progression in koalas and that the predicted hub genes could be promising prognostic biomarkers for pathogenesis.

Whole Genomic Constellation of Avian Reovirus Strains Isolated from Broilers with Arthritis in North Carolina, USA

Avian reovirus (ARV) is an emerging pathogen which causes significant economic challenges to the chicken and turkey industry in the USA and globally, yet the molecular characterization of most ARV strains is restricted to a single particular gene, the sigma C gene. The genome of arthrogenic reovirus field isolates (R18-37308 and R18-38167), isolated from broiler chickens in North Carolina (NC), USA in 2018, was sequenced using long-read next-generation sequencing (NGS). The isolates were genotyped based on the amino acid sequence of sigma C (σC) followed by phylogenetic and amino acid analyses of the other 11 genomically encoded proteins for whole genomic constellation and genetic variation detection. The genomic length of the NC field strains was 23,494 bp, with 10 dsRNA segments ranging from 3959 bp (L1) to 1192 bp (S4), and the 5' and 3' untranslated regions (UTRs) of all the segments were found to be conserved. R18-37308 and R18-38167 were found to belong to genotype (G) VI based on the σC analysis and showed nucleotide and amino acid sequence identity ranging from 84.91-98.47% and 83.43-98.46%, respectively, with G VI strains. Phylogenetic analyses of individual genes of the NC strains did not define a single common ancestor among the available completely sequenced ARV strains. Nevertheless, most sequences supported the Chinese strain LY383 as a probable ancestor of these isolates. Moreover, amino acid analysis revealed multiple amino acid substitution events along the entirety of the genes, some of which were unique to each strain, which suggests significant divergence owing to the accumulation of point mutations. All genes from R18-37308 and R18-38167 were found to be clustered within genotypic clusters that included only ARVs of chicken origin, which negates the possibility of genetic pooling or host variation. Collectively, this study revealed sequence divergence between the NC field strains and reference ARV strains, including the currently used vaccine strains could help updating the vaccination regime through the inclusion of these highly divergent circulating indigenous field isolates.

A mutation-induced drug resistance database (MdrDB)

Mutation-induced drug resistance is a significant challenge to the clinical treatment of many diseases, as structural changes in proteins can diminish drug efficacy. Understanding how mutations affect protein-ligand binding affinities is crucial for developing new drugs and therapies. However, the lack of a large-scale and high-quality database has hindered the research progresses in this area. To address this issue, we have developed MdrDB, a database that integrates data from seven publicly available datasets, which is the largest database of its kind. By integrating information on drug sensitivity and cell line mutations from Genomics of Drug Sensitivity in Cancer and DepMap, MdrDB has substantially expanded the existing drug resistance data. MdrDB is comprised of 100,537 samples of 240 proteins (which encompass 5119 total PDB structures), 2503 mutations, and 440 drugs. Each sample brings together 3D structures of wild type and mutant protein-ligand complexes, binding affinity changes upon mutation (ΔΔG), and biochemical features. Experimental results with MdrDB demonstrate its effectiveness in significantly enhancing the performance of commonly used machine learning models when predicting ΔΔG in three standard benchmarking scenarios. In conclusion, MdrDB is a comprehensive database that can advance the understanding of mutation-induced drug resistance, and accelerate the discovery of novel chemicals.

The Impact of Smoking on Peri-implant Microbiota: A Systematic Review

OBJECTIVES

Peri-implantitis is associated with bacterial plaque biofilms and with patients who have a history of periodontitis. Smoking is a risk factor for periodontitis, but the relationship between smoking and peri-implantitis is unclear. The aim of this systematic review was to assess evidence ascertaining the relationship between smoking and peri-implant microbiota.

DATA SOURCES

An electronic search was conducted in the MEDLINE/PubMed, Embase and Scopus® databases in duplicate up to January 2023 without language restrictions. Studies were considered eligible for inclusion if they involved evaluation of the peri-implant microbiota of smokers and nonsmokers. Methodological quality was assessed with the adapted Newcastle-Ottawa scale.

STUDY SELECTION

Fourteen studies were identified for inclusion in the present study, and 85.7% of the studies were defined as medium to high methodological quality. Overall, the evidence presented in this review was limited to medium to high methodological quality. The data indicates that significantly higher frequencies of anaerobic pathogens are detectable in healthy peri-implant tissues of smokers. A lower diversity of microbiota was observed in healthy peri-implant sites of smokers. In the transition from clinically healthy to a diseased status, smoking shaped a reduced peri-implant microbiota by depleting commensal and enriching pathogenic species.

CONCLUSIONS

The composition of peri-implant microbiota may be influenced by smoking. More studies are needed to determine the impact of smoking on peri-implant microbiota.

CLINICAL SIGNIFICANCE

In the transition from clinically healthy to a diseased status, smoking shaped a reduced peri-implant microbiota by depleting commensal and enriching pathogenic species. The composition of peri-implant microbiota may be influenced by smoking.

Diversity and community structure of ectomycorrhizal mycorrhizal fungi in roots and rhizosphere soil of Abies koreana and Taxus cuspidata in Mt. Halla

In this study, the roots and rhizosphere soil of Abies koreana and Taxus cuspidata were collected from sites at two different altitudes on Mt. Halla. Ectomycorrhizal fungi (EMF) were identified by Illumina MiSeq sequencing. The proportion of EMF from the roots was 89% in A. koreana and 69% in T. cuspidata. Among EMF in rhizosphere soils, the genus Russula was the most abundant in roots of A. koreana (p < 0.05). The altitude did not affect the biodiversity of EMF communities but influenced fungal community composition. However, the host plants had the most significant effect on EMF communities. The result of the EMF community analysis showed that even if the EMF were isolated from the same altitudes, the EMF communities differed according to the host plant. The community similarity index of EMF in the roots of A. koreana was higher than that of T. cuspidata (p < 0.05). The results show that both altitude and host plants influenced the structure of EMF communities. Conifers inhabiting harsh sub-alpine environments rely strongly on symbiotic relationships with EMF. A. koreana is an endangered species with a higher host specificity of EMF and climate change vulnerability than T. cuspidata. This study provides insights into the EMF communities, which are symbionts of A. koreana, and our critical findings may be used to restore A. koreana.

Complete genome sequence analysis of a plant growth-promoting phylloplane Bacillus altitudinis FD48 offers mechanistic insights into priming drought stress tolerance in rice

Bacillus altitudinis FD48 is a multifunctional plant growth-promoting bacterium isolated from the phylloplane of rice and survives at --10 bars of osmotic potential (--1.0 MPa). It also serves as an ideal PGPM against drought stress by triggering antioxidant defense mechanisms in rice. To further unravel the genetic determinants of osmotic stress tolerance and plant growth-promoting traits, the whole genome sequence of FD48 was compared with its related strains. The whole genome analysis revealed a single chromosome with a total length of 3,752,533 bp (3.7 Mb) and an average G + C ratio of 41.19%. A total of 4029 genes were predicted, of which 3964 (98.4%) were protein-encoding genes (PEGs) and 65 (1.6%) were non-protein-coding genes. The interaction of FD48 with the host plants is associated with many chemotactic and motility-related genes. The ability of FD48 to colonize plants and maintain plant growth under adverse environmental conditions was evidenced by the presence of genes for plant nutrient acquisition, phytohormone synthesis, trehalose, choline, and glycine betaine biosynthesis, microbial volatile organic compounds (acetoin synthesis), heat and cold shock chaperones, translation elongation factor TU (Ef-Tu), siderophore production, DEAD/DEAH boxes, and non- ribosomal peptide synthase clusters (bacilysin, fengycin, and bacitracin). This study sheds light on the drought stress-resilient mechanism, metabolic pathways and potential activity, and plant growth-promoting traits of B. altitudinis FD48 at the genetic level.

Combined multi-omics analysis reveals oil mist particulate matter-induced lung injury in rats: Pathological damage, proteomics, metabolic disturbances, and lung dysbiosis

Oil mist particulate matter (OMPM) causes acute and chronic diseases and exacerbations. Owing to the characteristics of poor ventilation, high oil mist concentration, and a relatively closed working environment, the existence of OMPM in the cabin is inevitable, and its impact on the health of occupations on ships cannot be ignored. However, compared with several studies that summarized the health effects of OMPM from traditional sources, few studies have focused on the occupational exposure risk of OMPM from oil pollution sources in ships. In this study, we collected OMPM from oil pollution in cabins and assessed the exposure to OMPM from oil pollution and the corresponding health risks through acute exposure experiments in rats. OMPM exposure induces protein regulation in the extracellular matrix and immune responses, leading to severe inflammatory responses. The abundance and composition of the lung microbial community changed significantly. It interferes with the lung metabolite levels. However, more research is needed to fully understand the extent of health risks associated with OMPM exposure. Further research on vulnerable groups exposed to OMPM from ships is needed to inform public health interventions.

Metabolic properties, gene functions, and biosafety analysis reveal the action of three rhizospheric plant growth-promoting bacteria of Jujuncao (Pennisetum giganteum)

This study aimed to identify the specific genes associated with plant growth promotion and cadmium tolerance in three bacteria strains associated with Pennisetum giganteum as well as to determine their biosafety levels in their potential use as biofertilizers for promoting plant growth and phytoremediation activities. The plant growth-promoting (PGP) abilities of Enterobacter cloacae strain RCB980 (A3), Klebsiella pneumonia strain kpa (A4), and Klebsiella sp. strain XT-2 (A7) were determined by a growth promotion trial and through testing for PGP traits such as 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase enzyme production, phosphorus solubilization, siderophore synthesis, and indole-3 acetic acid (IAA) production. The genes that potentially contribute to the beneficial activities of these three strains were identified through an analysis of their genomes. To establish the biosafety of the candidate PGPB, a pathological study was undertaken whereby 20 Kunming mice were injected intraperitoneally to study and analyze the effects of the strains on growth and lung paraffin sections of the mice. The strains had no obvious toxicity effect on the tested mice and were therefore not considered as highly virulent strains. These strains are thus considered non-toxic, safe, and highly recommended for use in environmental remediation strategies and agricultural production.

Fungal secondary metabolites in food and pharmaceuticals in the era of multi-omics

Fungi produce several bioactive metabolites, pigments, dyes, antioxidants, polysaccharides, and industrial enzymes. Fungal products are also the primary sources of functional food and nutrition, and their pharmacological products are used for healthy aging. Their molecular properties are validated through the use of recent high-throughput genomic, transcriptomic, and metabolomic tools and techniques. Together, these updated multi-omic tools have been used to study fungal metabolites structure and their mode of action on biological and cellular processes. Diverse groups of fungi produce different proteins and secondary metabolites, which possess tremendous biotechnological and pharmaceutical applications. Furthermore, its use and acceptability can be accelerated by adopting multi-omics, bioinformatics, and machine learning tools that generate a huge amount of molecular data. The integration of artificial intelligence and machine learning tools in the era of omics and big data has opened up a new outlook in both basic and applied researches in the area of nutraceuticals and functional food and nutrition. KEY POINTS: • Multi-omic tool helps in the identification of novel fungal metabolites • Intra-omic data from genomics to bioinformatics • Novel metabolites and application in human health.

MOrPH-PhD: A Phage Display System for the Functional Selection of Genetically Encoded Macrocyclic Peptides

Macrocyclic peptides represent promising scaffolds for targeting biomolecules with high affinity and selectivity, making methods for the diversification and functional selection of these macrocycles highly valuable for drug discovery purposes. We recently reported a novel phage display platform (called MOrPH-PhD) for the creation and functional exploration of combinatorial libraries of genetically encoded cyclic peptides. In this system, spontaneous, posttranslational peptide cyclization by means of a cysteine-reactive non-canonical amino acid is integrated with M13 bacteriophage display, enabling the creation of genetically encoded macrocyclic peptide libraries displayed on phage particles. Using this system, it is possible to rapidly generate and screen large libraries of phage-displayed macrocyclic peptides (up to 10⁸ to 10¹⁰ members) in order to identify high-affinity binders of a target protein of interest. Herein, we describe step-by-step protocols for the production of MOrPH-PhD libraries, the screening of these libraries against an immobilized protein target, and the isolation and characterization of functional macrocyclic peptides from these genetically encoded libraries.

Validation of predicted anonymous proteins simply using Fisher's exact test

Motivation

Genomes sequencing has become the primary (and often the sole) experimental method to characterize newly discovered organisms, in particular from the microbial world (bacteria, archaea, viruses). This generates an ever increasing number of predicted proteins the existence of which is unwarranted, in particular among those without homolog in model organisms. As a last resort, the computation of the selection pressure from pairwise alignments of the corresponding 'Open Reading Frames' (ORFs) can be used to validate their existences. However, this approach is error-prone, as not usually associated with a significance test.

Results

We introduce the use of the straightforward Fisher's exact test as a postprocessing of the results provided by the popular CODEML sequence comparison software. The respective rates of nucleotide changes at the nonsynonymous versus synonymous position (as determined by CODEML) are turned into entries into a 2 × 2 contingency table, the probability of which is computed under the Null hypothesis that they should not behave differently if the ORFs do not encode actual proteins. Using the genome sequences of two recently isolated giant viruses, we show that strong negative selection pressures do not always provide a solid argument in favor of the existence of proteins.

Novel Enzymes From the Red Sea Brine Pools: Current State and Potential

The Red Sea is a marine environment with unique chemical characteristics and physical topographies. Among the various habitats offered by the Red Sea, the deep-sea brine pools are the most extreme in terms of salinity, temperature and metal contents. Nonetheless, the brine pools host rich polyextremophilic bacterial and archaeal communities. These microbial communities are promising sources for various classes of enzymes adapted to harsh environments - extremozymes. Extremozymes are emerging as novel biocatalysts for biotechnological applications due to their ability to perform catalytic reactions under harsh biophysical conditions, such as those used in many industrial processes. In this review, we provide an overview of the extremozymes from different Red Sea brine pools and discuss the overall biotechnological potential of the Red Sea proteome.

Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study

Assessing the reproducibility, accuracy and utility of massively parallel DNA sequencing platforms remains an ongoing challenge. Here the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Study benchmarks the performance of a set of sequencing instruments (HiSeq/NovaSeq/paired-end 2 × 250-bp chemistry, Ion S5/Proton, PacBio circular consensus sequencing (CCS), Oxford Nanopore Technologies PromethION/MinION, BGISEQ-500/MGISEQ-2000 and GS111) on human and bacterial reference DNA samples. Among short-read instruments, HiSeq 4000 and X10 provided the most consistent, highest genome coverage, while BGI/MGISEQ provided the lowest sequencing error rates. The long-read instrument PacBio CCS had the highest reference-based mapping rate and lowest non-mapping rate. The two long-read platforms PacBio CCS and PromethION/MinION showed the best sequence mapping in repeat-rich areas and across homopolymers. NovaSeq 6000 using 2 × 250-bp read chemistry was the most robust instrument for capturing known insertion/deletion events. This study serves as a benchmark for current genomics technologies, as well as a resource to inform experimental design and next-generation sequencing variant calling.

Characterisation of Early Positive mcr-1 Resistance Gene and Plasmidome in Escherichia coli Pathogenic Strains Associated with Variable Phylogroups under Colistin Selection

An antibiotic susceptibility monitoring programme was conducted from 2004 to 2010, resulting in a collection of 143 Escherichia coli cultured from bovine faecal samples (diarrhoea) and milk-aliquots (mastitis). The isolates were subjected to whole-genome sequencing and were distributed in phylogroups A, B1, B2, C, D, E, and G with no correlation for particular genotypes with pathotypes. In fact, the population structure showed that the strains belonging to the different phylogroups matched broadly to ST complexes; however, the isolates are randomly associated with the diseases, highlighting the necessity to investigate the virulence factors more accurately in order to identify the mechanisms by which they cause disease. The antimicrobial resistance was assessed phenotypically, confirming the genomic prediction on three isolates that were resistant to colistin, although one isolate was positive for the presence of the gene mcr-1 but susceptible to colistin. To further characterise the genomic context, the four strains were sequenced by using a single-molecule long read approach. Genetic analyses indicated that these four isolates harboured complex and diverse plasmids encoding not only antibiotic resistant genes (including mcr-1 and bla) but also virulence genes (siderophore, ColV, T4SS). A detailed description of the plasmids of these four E. coli strains, which are linked to bovine mastitis and diarrhoea, is presented for the first time along with the characterisation of the predicted antibiotic resistance genes. The study highlighted the diversity of incompatibility types encoding complex antibiotic resistance elements such as Tn6330, ISEcp1, Tn6029, and IS5075. The mcr-1 resistance determinant was identified in IncHI2 plasmids pCFS3273-1 and pCFS3292-1, thus providing some of the earliest examples of mcr-1 reported in Europe, and these sequences may be a representative of the early mcr-1 plasmidome characterisation in the EU/EEA.

Empirical evaluation of methods for de novo genome assembly

Technologies for next-generation sequencing (NGS) have stimulated an exponential rise in high-throughput sequencing projects and resulted in the development of new read-assembly algorithms. A drastic reduction in the costs of generating short reads on the genomes of new organisms is attributable to recent advances in NGS technologies such as Ion Torrent, Illumina, and PacBio. Genome research has led to the creation of high-quality reference genomes for several organisms, and de novo assembly is a key initiative that has facilitated gene discovery and other studies. More powerful analytical algorithms are needed to work on the increasing amount of sequence data. We make a thorough comparison of the de novo assembly algorithms to allow new users to clearly understand the assembly algorithms: overlap-layout-consensus and de-Bruijn-graph, string-graph based assembly, and hybrid approach. We also address the computational efficacy of each algorithm's performance, challenges faced by the assem- bly tools used, and the impact of repeats. Our results compare the relative performance of the different assemblers and other related assembly differences with and without the reference genome. We hope that this analysis will contribute to further the application of de novo sequences and help the future growth of assembly algorithms.

Acetate kinase and peptidases are associated with the proteolytic activity of Lactobacillus helveticus isolated from fermented food

Lactobacillus (L.) helveticus is widely used in food industry due to its high proteolytic activity. However, such activity varies greatly between isolates, and the determining factors regulating the strength of proteolytic activity in L. helveticus are unclear. This study sequenced the genomes of 60 fermented food-originated L. helveticus and systemically examined the proteolytic activity-determining factors. Our analyses found that the strength of proteolytic activity in L. helveticus was independent of the isolation source, geographic location, phylogenetic closeness between isolates, and distribution of cell envelope proteinases (CEPs). Genome-wide association study (GWAS) identified two genes, the acetate kinase (ackA) and a hypothetical protein, and 15 single nucleotide polymorphisms (SNPs) that were associated with the strength of the proteolytic activity. Further investigating the functions of these gene components revealed that ackA and two cysteine peptidases coding genes (pepC and srtA) rather than the highly heterogeneous and intraspecific CEPs were linked to the level of proteolytic activity. Moreover, the sequence type (ST) defined by SNP analysis revealed a total of ten STs, and significantly weaker proteolytic activity was observed among isolates of ST2. This study provides practical information for future selection of L. helveticus of strong proteolytic activity.

Screening for Candidate Genes Associated with Biocontrol Mechanisms of Bacillus pumilus DX01 Using Tn5 Transposon Mutagenesis and a 2-DE-Based Comparative Proteomic Analysis

A total of 1467 mutants of the biocontrol bacterium Bacillus pumilus DX01 were obtained by Tn5 insertional mutagenesis and subjected to the determination of antagonistic capabilities. Compared with the wild-type strain DX01, the mutant M25 was identified to have the most significant reduction in antagonistic capability against the phytopathogen Bipolaris maydis and extracellular proteinase activity. The integration site of the exogenous T-DNA in the genome of mutant M25 was revealed in the coding region of malony CoA-ACP transacylase (MCAT) gene (mcat), which belongs to a polyketide synthase (PKS) gene cluster, DX01pks of B. pumilus DX01. Furthermore, the whole DX01pks gene cluster was cloned using Illumina Solexa sequencing technology, and it has a modular framework different from the other two gene clusters involved in polyketide synthesis in B. amyloliquefaciens FZB42 (pks1) and B. subtilis 168 (pksX). Finally, in order to gain more insights into the molecular mechanisms of biocontrol of B. pumilus DX01, the changes in the relative level of expression of total proteins between the original strain DX01 and the mutant M25 were detected by 2-DE-based proteomic analysis. A total of twenty differentially expressed proteins were identified upon the mcat gene transposition mutagenesis. Of these proteins, seven proteins were up-regulated in expression level and the other proteins were down-regulated. Taken together, the results in this study showed that Tn5 transposon mutagenesis of B. pumilus DX01 can lead to a significant change of antiphytopathogen ability, and the DX01pks gene cluster possibly play a potential role in the biocontrol processes of this bacterium.

De novo assembly of Auricularia polytricha transcriptome and discovery of genes involved in the degradation of lignocellulose

Auricularia polytricha belonging to Basidiomycota has the ability to degrade lignocellulose. However, there has been no resource in public databases examining the transcriptome of A. polytricha. In this study, high-throughput sequencing platform BGISEQ-500 was used to generate large amount of transcript sequences from A. polytricha for gene discovery and molecular marker development. A total of 28,102 unigenes were discovered from the assembly of clean reads. In addition, functional categorization of the gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) metabolic pathways revealed several important biological processes. GO annotation analysis presented 47 categories, with the major subcategories being catalytic activity, binding, cellular process, metabolic process, and cell. Among the five functional categories and 21 subcategories of processes discovered from KEGG, global and overview maps, carbohydrate metabolism, transport, and catabolism are the main subcategories. Furthermore, among the unigenes related to lignocellulosic degradation discovered by KEGG pathway enrichment analysis, 2, 5, and 16 unigenes in de novo assembly of A. polytricha transcriptome were found to relate to cellulose, hemicellulose, and lignin degradation, respectively. The study provided valuable information on the degradation of lignocellulose to facilitate research on the degradation mechanism, molecular marker, functional research, gene mapping, and other multigenomic studies of species containing lignocellulose.

Comprehensive transcriptomic and proteomic analyses of antroquinonol biosynthetic genes and enzymes in Antrodia camphorata

Antroquinonol (AQ) has several remarkable bioactivities in acute myeloid leukaemia and pancreatic cancer, but difficulties in the mass production of AQ hamper its applications. Currently, molecular biotechnology methods, such as gene overexpression, have been widely used to increase the production of metabolites. However, AQ biosynthetic genes and enzymes are poorly understood. In this study, an integrated study coupling RNA-Seq and isobaric tags for relative and absolute quantitation (iTRAQ) were used to identify AQ synthesis-related genes and enzymes in Antrodia camphorata during coenzyme Q0-induced fermentation (FM). The upregulated genes related to acetyl-CoA synthesis indicated that acetyl-CoA enters the mevalonate pathway to form the farnesyl tail precursor of AQ. The metE gene for an enzyme with methyl transfer activity provided sufficient methyl groups for AQ structure formation. The CoQ2 and ubiA genes encode p-hydroxybenzoate polyprenyl transferase, linking coenzyme Q0 and the polyisoprene side chain to form coenzyme Q3. NADH is transformed into NAD+ and releases two electrons, which may be beneficial for the conversion of coenzyme Q3 to AQ. Understanding the biosynthetic genes and enzymes of AQ is important for improving its production by genetic means in the future.

Dysbiosis is not present in horses with fecal water syndrome when compared to controls in spring and autumn

BACKGROUND

Fecal water syndrome (FWS) is long-standing and common in horses, particularly in central Europe. No large epidemiological data sets exist, and the cause remains elusive. Dysbiosis could play a role in pathogenesis.

OBJECTIVES

To evaluate whether dysbiosis is present in horses with FWS when compared to stable-matched control horses in spring and autumn.

ANIMALS

Fecal samples were collected from horses with FWS (n = 16; 9 mares, 7 geldings) and controls (n = 15; 8 mares, 7 geldings).

METHODS

The bacterial microbiome of samples collected in spring and autumn of 2016 was analyzed using high-throughput sequencing. Differences in relative abundance of bacterial taxa, alpha diversity, and beta diversity indices were assessed between horses with FWS and controls based on season.

RESULTS

Differences in microbial community composition based on time point and health status were not observed on any taxonomic level. Limited differences were seen on linear discriminant analysis effect size analysis. No difference in alpha diversity indices was observed including richness, diversity based on health status, or time point. No effect of health status on microbial community membership structure was observed.

CONCLUSIONS AND CLINICAL IMPORTANCE

Limited differences were found in the bacterial microbiota of horses with and without FWS, regardless of season. Further research is needed to elucidate the role of microbiota in the development of FWS.

dbAMP: an integrated resource for exploring antimicrobial peptides with functional activities and physicochemical properties on transcriptome and proteome data

Antimicrobial peptides (AMPs), naturally encoded from genes and generally contained 10–100 amino acids, are crucial components of the innate immune system and can protect the host from various pathogenic bacteria, as well as viruses. In recent years, the widespread use of antibiotics has inspired the rapid growth of antibiotic-resistant microorganisms that usually induce critical infection and pathogenesis. An increasing interest therefore was motivated to explore natural AMPs that enable the development of new antibiotics. With the potential of AMPs being as new drugs for multidrug-resistant pathogens, we were thus motivated to develop a database (dbAMP, http://csb.cse.yzu.edu.tw/dbAMP/) by accumulating comprehensive AMPs from public domain and manually curating literature. Currently in dbAMP there are 12 389 unique entries, including 4271 experimentally verified AMPs and 8118 putative AMPs along with their functional activities, supported by 1924 research articles. The advent of high-throughput biotechnologies, such as mass spectrometry and next-generation sequencing, has led us to further expand dbAMP as a database-assisted platform for providing comprehensively functional and physicochemical analyses for AMPs based on the large-scale transcriptome and proteome data. Significant improvements available in dbAMP include the information of AMP–protein interactions, antimicrobial potency analysis for ‘cryptic’ region detection, annotations of AMP target species, as well as AMP detection on transcriptome and proteome datasets. Additionally, a Docker container has been developed as a downloadable package for discovering known and novel AMPs on high-throughput omics data. The user-friendly visualization interfaces have been created to facilitate peptide searching, browsing, and sequence alignment against dbAMP entries. All the facilities integrated into dbAMP can promote the functional analyses of AMPs and the discovery of new antimicrobial drugs.

Specificity Analysis of Genome Based on Statistically Identical K-Words With Same Base Combination

Goal: Individual characteristics are determined through a genome consisting of a complex base combination. This base combination is reflected in the k-word profile, which represents the number of consecutive k bases. Therefore, it is important to analyze the genome-specific statistical specificity in the k-word profile to understand the characteristics of the genome. In this paper, we propose a new k-word-based method to analyze genome-specific properties. Methods: We define k-words consisting of the same number of bases as statistically identical k-words. The statistically identical k-words are estimated to appear at a similar frequency by statistical prediction. However, this may not be true in the genome because it is not a random list of bases. The ratio between frequencies of two statistically identical k-words can then be used to investigate the statistical specificity of the genome reflected in the k-word profile. In order to find important ratios representing genomic characteristics, a reference value is calculated that results in a minimum error when classifying data by ratio alone. Finally, we propose a genetic algorithm-based search algorithm to select a minimum set of ratios useful for classification. Results: The proposed method was applied to the full-length sequence of microorganisms for pathogenicity classification. The classification accuracy of the proposed algorithm was similar to that of conventional methods while using only a few features. Conclusions: We proposed a new method to investigate the genome-specific statistical specificity in the k-word profile which can be applied to find important properties of the genome and classify genome sequences.

Genome-Wide Profiling of Enterotoxigenic Staphylococcus aureus Strains Used for the Production of Naturally Contaminated Cheeses

Staphylococcus aureus is a major human pathogen and an important cause of livestock infections. More than 20 staphylococcal enterotoxins with emetic activity can be produced by specific strains responsible for staphylococcal food poisoning, one of the most common food-borne diseases. Whole genome sequencing provides a comprehensive view of the genome structure and gene content that have largely been applied in outbreak investigations and genomic comparisons. In this study, six enterotoxigenic S. aureus strains were characterised using a combination of molecular, phenotypical and computational methods. The genomes were analysed for the presence of virulence factors (VFs), where we identified 110 genes and classified them into five categories: adherence (n = 31), exoenzymes (n = 28), genes involved in host immune system evasion (n = 7); iron uptake regulatory system (n = 8); secretion machinery factors and toxins' genes (n = 36), and 39 genes coding for transcriptional regulators related to staphylococcal VFs. Each group of VFs revealed correlations among the six enterotoxigenic strains, and further analysis revealed their accessory genomic content, including mobile genetic elements. The plasmids pLUH02 and pSK67 were detected in the strain ProNaCC1 and ProNaCC7, respectively, carrying out the genes sed, ser, and selj. The genes carried out by prophages were detected in the strain ProNaCC2 (see), ProNaCC4, and ProNaCC7 (both positive for sea). The strain ProNaCC5 resulted positive for the genes seg, sei, sem, sen, seo grouped in an exotoxin gene cluster, and the strain ProNaCC6 resulted positive for seh, a transposon-associated gene. The six strains were used for the production of naturally contaminated cheeses which were tested with the European Screening Method for staphylococcal enterotoxins. The results obtained from the analysis of toxins produced in cheese, combined with the genomic features represent a portrait of the strains that can be used for the production of staphylococcal enterotoxin-positive cheese as reference material.

Comprehensive genomic analysis of an indigenous Pseudomonas pseudoalcaligenes degrading phenolic compounds

Environmental contamination with aromatic compounds is a universal challenge. Aromatic-degrading microorganisms isolated from the same or similar polluted environments seem to be more suitable for bioremediation. Moreover, microorganisms adapted to contaminated environments are able to use toxic compounds as the sole sources of carbon and energy. An indigenous strain of Pseudomonas, isolated from the Mahshahr Petrochemical plant in the Khuzestan province, southwest of Iran, was studied genetically. It was characterized as a novel Gram-negative, aerobic, halotolerant, rod-shaped bacterium designated Pseudomonas YKJ, which was resistant to chloramphenicol and ampicillin. Genome of the strain was completely sequenced using Illumina technology to identify its genetic characteristics. MLST analysis revealed that the YKJ strain belongs to the genus Pseudomonas indicating the highest sequence similarity with Pseudomonas pseudoalcaligenes strain CECT 5344 (99% identity). Core- and pan-genome analysis indicated that P. pseudoalcaligenes contains 1,671 core and 3,935 unique genes for coding DNA sequences. The metabolic and degradation pathways for aromatic pollutants were investigated using the NCBI and KEGG databases. Genomic and experimental analyses showed that the YKJ strain is able to degrade certain aromatic compounds including bisphenol A, phenol, benzoate, styrene, xylene, benzene and chlorobenzene. Moreover, antibiotic resistance and chemotaxis properties of the YKJ strain were found to be controlled by two-component regulatory systems.

Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling

The aim of this work was to analyze and compare the bacterial communities of 663 samples from a Brazilian hospital by using high-throughput sequencing of the 16S rRNA gene. To increase taxonomic profiling and specificity of 16S-based identification, a strict sequence quality filtering process was applied for the accurate identification of clinically relevant bacterial taxa. Our results indicate that the hospital environment is predominantly inhabited by closely related species. A massive dominance of a few taxa in all taxonomic levels down to the genera was observed, where the ten most abundant genera in each facility represented 64.4% of all observed taxa, with a major predominance of Acinetobacter and Pseudomonas. The presence of several nosocomial pathogens was revealed. Co-occurrence analysis indicated that the present hospital microbial network had low connectedness, forming a clustered topology, but not structured among groups of nodes (i.e., modules). Furthermore, we were able to detect ecologically relevant relationships between specific microbial taxa, in particular, potential competition between pathogens and non-pathogens. Overall, these results provide new insight into different aspects of a hospital microbiome and indicate that 16S rRNA sequencing may serve as a robust one-step tool for microbiological identification and characterization of a wide range of clinically relevant bacterial taxa in hospital settings with a high resolution.

Effects of tillage managements and maize straw returning on soil microbiome using 16S rDNA sequencing

Agricultural practices could affect bacterial diversity and community structure by altering soil physical and chemical properties. Straw returning and tillage practices are widely used in agriculture, however, the effects of these agricultural practices on microbiomes are still unclear. In the present study, we compared the 18 bacterial communities of soil with different straw returning and tillage treatment combinations. The V3-V4 regions of the 16S ribosomal RNA were amplified and analyzed by high-throughput sequencing technology. The results showed that the bacterial communities were consistently dominated by Acidobacteria, Proteobacteria, Actinobacteria, and Chloroflexi. Short-term straw returning and tillage practices significantly altered the diversity, relative abundance and functions of the soil microbiome. Soil subjected to rotary tillage and straw returning (RTS) combination possessed the highest bacterial diversity and lowest ratio of G+/G- bacteria, indicating that RTS could be an efficient integrated management system to improve microbiome in the short term. Double verifications based on relative abundance and network analysis, revealed close relationships of Mycobacterium and Methylibium with RTS, indicating they could serve as biomarkers for RTS. Investigating microbial changes under different agricultural practices will provide valuable foundations for land sustainable utilization and increase crop yields.

Titanium Ions Inhibit the Bacteria in Vase Solutions of Freshly Cut Gerbera jamesonii and Extend the Flower Longevity

Titanium ions significantly promote plant growth, but the mechanism is still unclear. Cut flowers are ideal materials for the study of plant growth and senescence. In this study, freshly cut Gerbera jamesonii were used to study the effects of titanium ions (8 mg/L) on the flower longevity. Flowering observation showed that the gerbera vase life was significantly prolonged in the presence of titanium ions. Plate colony counts showed that the amounts of bacteria in the vase solution of the control group were approximately 1700 times more than that of titanium ion treatment group. High-throughput sequencing was used to determine the sequences of 16S rRNA gene V3-V4 variable regions of the vase solutions to analyze bacterial species, their average proportions, and absolute abundance. The results showed that the titanium ions reduced the entire bacterial counts as well as altered the absolute abundance of different bacterial species in the vase solution. The most prevalent bacteria were mainly Enterobacteriaceae, Pseudomonas veronii, Pseudomonas sp., Delftia sp., Agrobacterium sp., Sphingobacterium multivorum, Acinetobacter johnsonii, and Clostridiaceae. In combination with plate colony counts, we demonstrated that all the bacterial growths were significantly inhibited by titanium ions, regardless of their average proportions increased or decreased. These results showed that titanium ions could extend effectively the longevity of gerberas and possess the broad-spectrum antibacterial properties. This study provides a basis for further mechanism exploration of titanium ions action and its applications in cut flower preservation and agricultural production.

Comparative transcriptome analysis reveals relationship of three major domesticated varieties of Auricularia auricula-judae

Auricularia auricula-judae is an edible mushroom and a traditional medicine in China as well as the fourth largest cultivated mushroom species in the world. Here for the first time, we present comparative transcriptome analyses of the fruiting bodies of three morphologically distinguishable A. auricula-judae cultivated varieties (Wujin, smooth; Banjin, partially wrinkled; and Quanjin, fully wrinkled) collected from Jilin Province, China. Biological triplicates were performed to determine the expression levels of 13,937 unigenes. Among them, only 13 unigenes were annotated to A. auricula-judae, highlighting the lack of publicly available reference sequences for this economically important species. Principal component analysis (PCA) determined that the gene expression profile of Quanjin was unique when compared to those of Banjin and Wujin. Such relationships were further supported by analyses of annotated and unannotated unigenes, differentially expressed unigenes, gene ontology functions, and the family of peroxidase genes. Using the KEGG database, significant alternations in biological pathways were detected among the three cultivars. This work contributes a large set of A. auricula-judae sequences to public database, establishes the relationships among major cultivars, and provides molecular guidance for breeding and cultivation.

Application of Support Vector Machines in Viral Biology

Novel experimental and sequencing techniques have led to an exponential explosion and spiraling of data in viral genomics. To analyse such data, rapidly gain information, and transform this information to knowledge, interdisciplinary approaches involving several different types of expertise are necessary. Machine learning has been in the forefront of providing models with increasing accuracy due to development of newer paradigms with strong fundamental bases. Support Vector Machines (SVM) is one such robust tool, based rigorously on statistical learning theory. SVM provides very high quality and robust solutions to classification and regression problems. Several studies in virology employ high performance tools including SVM for identification of potentially important gene and protein functions. This is mainly due to the highly beneficial aspects of SVM. In this chapter we briefly provide lucid and easy to understand details of SVM algorithms along with applications in virology.

Assessment of Bioleaching Microbial Community Structure and Function Based on Next-Generation Sequencing Technologies

It is widely known that bioleaching microorganisms have to cope with the complex extreme environment in which microbial ecology relating to community structure and function varies across environmental types. However, analyses of microbial ecology of bioleaching bacteria is still a challenge. To address this challenge, numerous technologies have been developed. In recent years, high-throughput sequencing technologies enabling comprehensive sequencing analysis of cellular RNA and DNA within the reach of most laboratories have been added to the toolbox of microbial ecology. The next-generation sequencing technology allowing processing DNA sequences can produce available draft genomic sequences of more bioleaching bacteria, which provides the opportunity to predict models of genetic and metabolic potential of bioleaching bacteria and ultimately deepens our understanding of bioleaching microorganism. High-throughput sequencing that focuses on targeted phylogenetic marker 16S rRNA has been effectively applied to characterize the community diversity in an ore leaching environment. RNA-seq, another application of high-throughput sequencing to profile RNA, can be for both mapping and quantifying transcriptome and has demonstrated a high efficiency in quantifying the changing expression level of each transcript under different conditions. It has been demonstrated as a powerful tool for dissecting the relationship between genotype and phenotype, leading to interpreting functional elements of the genome and revealing molecular mechanisms of adaption. This review aims to describe the high-throughput sequencing approach for bioleaching environmental microorganisms, particularly focusing on its application associated with challenges.

Genome sequencing and assessment of plant growth-promoting properties of a Serratia marcescens strain isolated from vermicompost

Background

Plant-bacteria associations have been extensively studied for their potential in increasing crop productivity in a sustainable manner. Serratia marcescens is a species of Enterobacteriaceae found in a wide range of environments, including soil.

Results

Here we describe the genome sequencing and assessment of plant growth-promoting abilities of S. marcescens UENF-22GI, a strain isolated from mature cattle manure vermicompost. In vitro, S. marcescens UENF-22GI is able to solubilize P and Zn, to produce indole compounds (likely IAA), to colonize hyphae and counter the growth of two phytopathogenic fungi. Inoculation of maize with this strain remarkably increased seedling growth and biomass under greenhouse conditions. The S. marcescens UENF-22GI genome has 5 Mb, assembled in 17 scaffolds comprising 4662 genes (4528 are protein-coding). No plasmids were identified. S. marcescens UENF-22GI is phylogenetically placed within a clade comprised almost exclusively of non-clinical strains. We identified genes and operons that are likely responsible for the interesting plant-growth promoting features that were experimentally described. The S. marcescens UENF-22GI genome harbors a horizontally-transferred genomic island involved in antibiotic production, antibiotic resistance, and anti-phage defense via a novel ADP-ribosyltransferase-like protein and possible modification of DNA by a deazapurine base, which likely contributes to its competitiveness against other bacteria.

Conclusions

Collectively, our results suggest that S. marcescens UENF-22GI is a strong candidate to be used in the enrichment of substrates for plant growth promotion or as part of bioinoculants for agriculture.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5130-y) contains supplementary material, which is available to authorized users.

The Planktonic Core Microbiome and Core Functions in the Cattle Rumen by Next Generation Sequencing

The cow rumen harbors a great variety of diverse microbes, which form a complex, organized community. Understanding the behavior of this multifarious network is crucial in improving ruminant nutrient use efficiency. The aim of this study was to expand our knowledge by examining 10 Holstein dairy cow rumen fluid fraction whole metagenome and transcriptome datasets. DNA and mRNA sequence data, generated by Ion Torrent, was subjected to quality control and filtering before analysis for core elements. The taxonomic core microbiome consisted of 48 genera belonging to Bacteria (47) and Archaea (1). The genus Prevotella predominated the planktonic core community. Core functional groups were identified using co-occurrence analysis and resulted in 587 genes, from which 62 could be assigned to metabolic functions. Although this was a minimal functional core, it revealed key enzymes participating in various metabolic processes. A diverse and rich collection of enzymes involved in carbohydrate metabolism and other functions were identified. Transcripts coding for enzymes active in methanogenesis made up 1% of the core functions. The genera associated with the core enzyme functions were also identified. Linking genera to functions showed that the main metabolic pathways are primarily provided by Bacteria and several genera may serve as a “back-up” team for the central functions. The key actors in most essential metabolic routes belong to the genus Prevotella. Confirming earlier studies, the genus Methanobrevibacter carries out the overwhelming majority of rumen methanogenesis and therefore methane emission mitigation seems conceivable via targeting the hydrogenotrophic methanogenesis.

DeepSimulator: a deep simulator for Nanopore sequencing

Motivation

Oxford Nanopore sequencing is a rapidly developed sequencing technology in recent years. To keep pace with the explosion of the downstream data analytical tools, a versatile Nanopore sequencing simulator is needed to complement the experimental data as well as to benchmark those newly developed tools. However, all the currently available simulators are based on simple statistics of the produced reads, which have difficulty in capturing the complex nature of the Nanopore sequencing procedure, the main task of which is the generation of raw electrical current signals.

Results

Here we propose a deep learning based simulator, DeepSimulator, to mimic the entire pipeline of Nanopore sequencing. Starting from a given reference genome or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments performed across four species show that the signals generated by our context-dependent model are more similar to the experimentally obtained signals than the ones generated by the official context-independent pore model. In terms of the simulated reads, we provide a parameter interface to users so that they can obtain the reads with different accuracies ranging from 83 to 97%. The reads generated by the default parameter have almost the same properties as the real data. Two case studies demonstrate the application of DeepSimulator to benefit the development of tools in de novo assembly and in low coverage SNP detection.

Availability and implementation

The software can be accessed freely at: https://github.com/lykaust15/DeepSimulator.

Supplementary information

Supplementary data are available at Bioinformatics online.

Functional Transcriptomics for Bacterial Gene Detectives

Developments in transcriptomic technology and the availability of whole-genome-level expression profiles for many bacterial model organisms have accelerated the assignment of gene function. However, the deluge of transcriptomic data is making the analysis of gene expression a challenging task for biologists. Online resources for global bacterial gene expression analysis are not available for the majority of published data sets, impeding access and hindering data exploration. Here, we show the value of preexisting transcriptomic data sets for hypothesis generation. We describe the use of accessible online resources, such as SalComMac and SalComRegulon, to visualize and analyze expression profiles of coding genes and small RNAs. This approach arms a new generation of "gene detectives" with powerful new tools for understanding the transcriptional networks of Salmonella, a bacterium that has become an important model organism for the study of gene regulation. To demonstrate the value of integrating different online platforms, and to show the simplicity of the approach, we used well-characterized small RNAs that respond to envelope stress, oxidative stress, osmotic stress, or iron limitation as examples. We hope to provide impetus for the development of more online resources to allow the scientific community to work intuitively with transcriptomic data.

Nanopore sequencing and full genome de novo assembly of human cytomegalovirus TB40/E reveals clonal diversity and structural variations

BACKGROUND

Human cytomegalovirus (HCMV) has a double-stranded DNA genome of approximately 235 Kbp that is structurally complex including extended GC-rich repeated regions. Genomic recombination events are frequent in HCMV cultures but have also been observed in vivo. Thus, the assembly of HCMV whole genomes from technologies producing shorter than 500 bp sequences is technically challenging. Here we improved the reconstruction of HCMV full genomes by means of a hybrid, de novo genome-assembly bioinformatics pipeline upon data generated from the recently released MinION MkI B sequencer from Oxford Nanopore Technologies.

RESULTS

The MinION run of the HCMV (strain TB40/E) library resulted in ~ 47,000 reads from a single R9 flowcell and in ~ 100× average read depth across the virus genome. We developed a novel, self-correcting bioinformatics algorithm to assemble the pooled HCMV genomes in three stages. In the first stage of the bioinformatics algorithm, long contigs (N50 = 21,892) of lower accuracy were reconstructed. In the second stage, short contigs (N50 = 5686) of higher accuracy were assembled, while in the final stage the high quality contigs served as template for the correction of the longer contigs resulting in a high-accuracy, full genome assembly (N50 = 41,056). We were able to reconstruct a single representative haplotype without employing any scaffolding steps. The majority (98.8%) of the genomic features from the reference strain were accurately annotated on this full genome construct. Our method also allowed the detection of multiple alternative sub-genomic fragments and non-canonical structures suggesting rearrangement events between the unique (UL /US) and the repeated (T/IRL/S) genomic regions.

CONCLUSIONS

Third generation high-throughput sequencing technologies can accurately reconstruct full-length HCMV genomes including their low-complexity and highly repetitive regions. Full-length HCMV genomes could prove crucial in understanding the genetic determinants and viral evolution underpinning drug resistance, virulence and pathogenesis.

Effects of residual organics in municipal wastewater on hydrogenotrophic denitrifying microbial communities

Hydrogenotrophic denitrification is promising for tertiary nitrogen removal from municipal wastewater. To reveal the influence of residual organics in municipal wastewater on hydrogenotrophic denitrifiers, we adopted high-throughput 16S rRNA gene amplicon sequencing to examine microbial communities in hydrogenotrophic denitrification enrichments. Using effluent from a municipal wastewater treatment plant as water source, COD, nitrate and pH were controlled the same except for a gradient of biodegradable carbon (i.e., primary effluent (PE), secondary effluent (SE), or combined primary and secondary effluent (CE)). Inorganic synthetic water (IW) was used as a control. Hydrogenophaga, a major facultative autotroph, accounted for 17.1%, 5.3%, 32.7% and 12.9% of the sequences in PE, CE, SE and IW, respectively, implicating that Hydrogenophaga grew well with or without organics. Thauera, which contains likely obligate autotrophic denitrifiers, appeared to be the most dominant genera (23.6%) in IW and accounted for 2.5%, 4.6% and 8.9% in PE, CE and SE, respectively. Thermomonas, which is related to heterotrophic denitrification, accounted for 4.2% and 7.9% in PE and CE fed with a higher content of labile organics, respectively. In contrast, Thermomonas was not detected in IW and accounted for only 0.6% in SE. Our results suggest that Thermomonas are more competitive than Thauera in hydrogenotrophic denitrification with biodegradable organics. Moreover, facultative autotrophic denitrifiers, Hydrogenophaga, are accommodating to residual organic in effluent wastewater, thus we propose that hydrogenotrophic denitrification is amenable for tertiary nitrogen removal.

The malS-5'UTR weakens the ability of Salmonella enterica serovar Typhi to survive in macrophages by increasing intracellular ATP levels

Bacterial non-coding RNAs (ncRNAs), as important regulatory factors, are involved in many cellular processes, including virulence and protection against environmental stress. The 5' untranslated region (UTR) of malS (named malS-5'UTR), a regulatory ncRNA, increases the invasive capacity and influences histidine biosynthesis in Salmonella enterica serovar Typhi (S. Typhi). In this study, we found that overexpression of the malS-5'UTR decreased S. Typhi survival within macrophages. A microarray analysis of a strain overexpressing the malS-5'UTR revealed a significant increase in the mRNA levels of the atp operon. The intracellular ATP levels were elevated in the malS-5'UTR overexpression strain. Quantitative real-time polymerase chain reaction results showed that the malS-5'UTR downregulated the mRNA levels of phoP, phoQ, and mgtC. MgtC, its expression is regulated by PhoP/PhoQ two-component regulatory system, inhibits the F1F0 ATP synthase, thereby preventing the accumulation of ATP to non-physiological levels and the acidification of the cytoplasm within macrophages. Thus, we propose that the malS-5'UTR weakens the ability of S. Typhi to survive in macrophages, probably because of the accumulation of ATP within macrophages, by regulating the mRNA levels of mgtC and the atp operon in a phoP-dependent manner.

Evaluation of 24-locus MIRU-VNTR genotyping in Mycobacterium tuberculosis cluster investigations in four jurisdictions in the United States, 2006-2010

The U.S. Centers for Disease Control and Prevention (CDC) uses a combination of spacer oligonucleotide typing (spoligotyping) and mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR) analyses as part of the National TB Genotyping Service (NTGS). The NTGS expansion from 12-locus MIRU-VNTR (MIRU12) to 24-locus MIRU-VNTR (MIRU24) in 2009 enhanced the ability to discriminate Mycobacterium tuberculosis strains. In the current study, we investigated the MIRU24 concordance among epidemiologic-linked tuberculosis (TB) patients in four U.S. health jurisdictions. We also evaluated the programmatic benefits of combining MIRU24 and spoligotyping with epidemiologic evidence in identifying potential recent TB transmission. We examined 342 TB patients in 42 spoligotype/MIRU12 (PCRType) clusters (equivalent to 46 spoligotype/MIRU24 [GENType] clusters) to identify epidemiologic links among cases. GENType clusters, when compared to PCRType clusters, had 12 times higher odds of epidemiologic links being identified if patients were younger than 25 years and 3 times higher odds if patients resided in the same zip code, or had HIV infection. Sixty (18%) fewer PCRType-clustered patients would need investigations if clusters are defined using GENType instead of PCRType. An important advantage of defining clusters by MIRU24 is resource savings related to the reduced number of clustered cases needing investigation.

Deep sequencing approaches for the analysis of prokaryotic transcriptional boundaries and dynamics

The identification of the protein-coding regions of a genome is straightforward due to the universality of start and stop codons. However, the boundaries of the transcribed regions, conditional operon structures, non-coding RNAs and the dynamics of transcription, such as pausing of elongation, are non-trivial to identify, even in the comparatively simple genomes of prokaryotes. Traditional methods for the study of these areas, such as tiling arrays, are noisy, labour-intensive and lack the resolution required for densely-packed bacterial genomes. Recently, deep sequencing has become increasingly popular for the study of the transcriptome due to its lower costs, higher accuracy and single nucleotide resolution. These methods have revolutionised our understanding of prokaryotic transcriptional dynamics. Here, we review the deep sequencing and data analysis techniques that are available for the study of transcription in prokaryotes, and discuss the bioinformatic considerations of these analyses.

Elucidation of quantitative structural diversity of remarkable rearrangement regions, shufflons, in IncI2 plasmids

A multiple DNA inversion system, the shufflon, exists in incompatibility (Inc) I1 and I2 plasmids. The shufflon generates variants of the PilV protein, a minor component of the thin pilus. The shufflon is one of the most difficult regions for de novo genome assembly because of its structural diversity even in an isolated bacterial clone. We determined complete genome sequences, including those of IncI2 plasmids carrying mcr-1, of three Escherichia coli strains using single-molecule, real-time (SMRT) sequencing and Illumina sequencing. The sequences assembled using only SMRT sequencing contained misassembled regions in the shufflon. A hybrid analysis using SMRT and Illumina sequencing resolved the misassembled region and revealed that the three IncI2 plasmids, excluding the shufflon region, were highly conserved. Moreover, the abundance ratio of whole-shufflon structures could be determined by quantitative structural variation analysis of the SMRT data, suggesting that a remarkable heterogeneity of whole-shufflon structural variations exists in IncI2 plasmids. These findings indicate that remarkable rearrangement regions should be validated using both long-read and short-read sequencing data and that the structural variation of PilV in the shufflon might be closely related to phenotypic heterogeneity of plasmid-mediated transconjugation involved in horizontal gene transfer even in bacterial clonal populations.

Investigating right ovary degeneration in chick embryos by transcriptome sequencing

In asymmetric chick gonads, the left and right female gonads undergo distinct programs during development, generating a functional ovary on the left side only. Despite some progress being made in recent years, the mechanisms of molecular regulation remain incompletely understood, and little genomic information is available regarding the degeneration of the right ovary in the chick embryo testis. In this study, we performed transcriptome sequencing to investigate differentially expressed genes in the left and right ovaries and gene functions at two critical time points; embryonic days 6 (E6) and 10 (E10). Using high-throughput RNA-sequencing technologies, 539 and 1046 genes were identified as being significantly differentially expressed between 6R-VS-6L and 10R-VS-10L. Gene ontology analysis of the differentially expressed genes revealed enrichment in functional pathways. Among these, candidate genes associated with degeneration of the right ovary in the chick embryo were identified. Identification of a pathway involved in ovarian degeneration provides an important resource for the further study of its molecular mechanisms and functions.

Differential Gene Expression Network in Terpenoid Synthesis of Antrodia cinnamomea in Mycelia and Fruiting Bodies

Antodia cinnamomea, a precious brown-rot fungus endemic to Taiwan, has pharmaceutical applications due to its diverse array of metabolites. The terpenoids found in A. cinnamomea contribute to its most important bioactivities. We identified several terpenoid compounds in A. cinnamomea and revealed that their content in mycelium and fruiting body were significantly different. Using next-generation sequencing and an in-house transcriptome database, we identified several terpene synthase (TPS) candidates. After sequence analysis and functional characterization, 10 out of 12 candidates were found to have single or multiple terpene synthesis functions. Most of the terpenoid compounds were found to confer important bioactivities. RT-PCR results showed a positive correlation between terpene synthase expression pattern and terpenoid content. In addition, we identified several modification enzyme candidates that may be involved in the postmodification of terpenoid compounds with a genomic DNA scaffold, and a putative genetic network.