Hepatitis C virus (HCV) causes debilitating liver diseases, which may progress to cirrhosis and cancer, and claims 500,000 annual lives worldwide. While HCV epidemiology, pathophysiology, and therapy are being deeply studied, rare attention is given to reciprocal interactions between HCV infection , HCV-induced chronic liver diseases, and the human gut microbiome. As Egypt has the world’s highest prevalence of HCV infections, we launched this study to monitor differences in the gut microbial community composition of Egyptian HCV patients that may affect, or result from, the patients’ liver state.
To this end, we analyzed stool samples from six stage 4-HCV patients and eight healthy individuals by high-throughput 16S rRNA gene sequencing using Illumina MiSeq. Overall, the alpha-diversity of the healthy persons’ gut microbiomes was higher than those of the HCV patients. Whereas members of phylum Bacteroidetes were more abundant in HCV patients, healthy individuals had higher abundance of Firmicutes, Proteobacteria, and Actinobacteria. Genus-level analysis showed differential abundance of Prevotella and Faecalibacterium (higher in HCV patients) vs. Ruminococcus and Clostridium (healthy group), indicating that the higher abundance of Bacteroidetes in HCV patients is most likely due to Prevotella overabundance. The probiotic genus, Bifidobacterium, was only observed in the microbiotas of healthy individuals.
To the best of our knowledge, this study provides a first overview of major phyla and genera differentiating stage 4-HCV patients from healthy individuals and suggests possible microbiome remodeling in chronic hepatitis C, possibly shaped by bacterial translocation as well as the liver’s impaired role in digestion and protein synthesis. Future studies will investigate the microbiome composition and functional capabilities in more patients while tracing some potential biomarker taxa (e.g., Prevotella, Faecalibacterium vs. Bifidobacterium).
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The online version of this article (doi:10.1186/s13099-016-0124-2) contains supplementary material, which is available to authorized users.
Microbiome; Infectious diseases; Virology; Liver disease; Gastro-intestinal tract; High-throughput sequencing; Next-generation sequencing
The central rift of the Red Sea has 25 brine pools with different physical and geochemical characteristics. Atlantis II (ATIID), Discovery Deeps (DD) and Chain Deep (CD) are characterized by high salinity, temperature and metal content. Several studies reported microbial communities in these brine pools, but few studies addressed the brine pool sediments. Therefore, sediment cores were collected from ATIID, DD, CD brine pools and an adjacent brine-influenced site. Sixteen different lithologic sediment sections were subjected to shotgun DNA pyrosequencing to generate 1.47 billion base pairs (1.47 × 109 bp). We generated sediment-specific reads and attempted to annotate all reads. We report the phylogenetic and biochemical uniqueness of the deepest ATIID sulfur-rich brine pool sediments. In contrary to all other sediment sections, bacteria dominate the deepest ATIID sulfur-rich brine pool sediments. This decrease in virus-to-bacteria ratio in selected sections and depth coincided with an overrepresentation of mobile genetic elements. Skewing in the composition of viruses-to-mobile genetic elements may uniquely contribute to the distinct microbial consortium in sediments in proximity to hydrothermally active vents of the Red Sea and possibly in their surroundings, through differential horizontal gene transfer.
Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set of publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. We propose adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution.
virus; bacteriophage; genomics; metagenomics; ecology
Escherichia coli EDL933 is the prototypic strain for enterohemorrhagic E. coli serotype O157:H7, associated with deadly food-borne outbreaks. Because the publicly available sequence of the EDL933 genome has gaps and >6,000 ambiguous base calls, we here present an updated high-quality, unambiguous genome sequence with no assembly gaps.
Prophages are phages in lysogeny that are integrated into, and replicated as part of, the host bacterial genome. These mobile elements can have tremendous impact on their bacterial hosts’ genomes and phenotypes, which may lead to strain emergence and diversification, increased virulence or antibiotic resistance. However, finding prophages in microbial genomes remains a problem with no definitive solution. The majority of existing tools rely on detecting genomic regions enriched in protein-coding genes with known phage homologs, which hinders the de novo discovery of phage regions. In this study, a weighted phage detection algorithm, PhiSpy was developed based on seven distinctive characteristics of prophages, i.e. protein length, transcription strand directionality, customized AT and GC skew, the abundance of unique phage words, phage insertion points and the similarity of phage proteins. The first five characteristics are capable of identifying prophages without any sequence similarity with known phage genes. PhiSpy locates prophages by ranking genomic regions enriched in distinctive phage traits, which leads to the successful prediction of 94% of prophages in 50 complete bacterial genomes with a 6% false-negative rate and a 0.66% false-positive rate.
M1T1 strain, its diversification by phage acquisition, and the in vivo selection of more fit members of its community present an intriguing example of the emergence of hypervirulent forms of a human pathogen.
The resurgence of severe invasive group A streptococcal infections in the 1980s is a typical example of the reemergence of an infectious disease. We found that this resurgence is a consequence of the diversification of particular strains of the bacteria. Among these strains is a highly virulent subclone of serotype M1T1 that has exhibited unusual epidemiologic features and virulence, unlike all other streptococcal strains. This clonal strain, commonly isolated from both noninvasive and invasive infection cases, is most frequently associated with severe invasive diseases. Because of its unusual prevalence, global spread, and increased virulence, we investigated the unique features that likely confer its unusual properties. In doing so, we found that the increased virulence of this clonal strain can be attributed to its diversification through phage mobilization and its ability to sense and adapt to different host environments; accordingly, the fittest members of this diverse bacterial community are selected to survive and invade host tissue.
M1T1 strain; Streptococcus pyogenes; epidemiology; strain diversification; invasive; pathogenomics; phage mobilization; horizontal gene transfer; perspective
Mathematical models of metabolism from bacterial systems biology have proven their utility across multiple fields, for example metabolic engineering, growth phenotype simulation, and biological discovery. The usefulness of the models stems from their ability to compute a link between genotype and phenotype, but their ability to accurately simulate gene-gene interactions has not been investigated extensively. Here we assess how accurately a metabolic model for Escherichia coli computes one particular type of gene-gene interaction, synthetic lethality, and find that the accuracy rate is between 25% and 43%. The most common failure modes were incorrect computation of single gene essentiality and biological information that was missing from the model. Moreover, we performed virtual and biological screening against several synthetic lethal pairs to explore whether two-compound formulations could be found that inhibit the growth of Gram-negative bacteria. One set of molecules was identified that, depending on the concentrations, inhibits E. coli and S. enterica serovar Typhimurium in an additive or antagonistic manner. These findings pinpoint specific ways in which to improve the predictive ability of metabolic models, and highlight one potential application of systems biology to drug discovery and translational medicine.
Mathematical models of biochemical networks form a cornerstone of bacterial systems biology. Inconsistencies between simulation output and experimental data point to gaps in knowledge about the fundamental biology of the organism. One such inconsistency centers on the gene aldA in Escherichia coli: it is essential in a computational model of E. coli metabolism, but experimentally it is not. Here, we reconcile this disparity by providing evidence that aldA and prpC form a synthetic lethal pair, as the double knockout could only be created through complementation with a plasmid-borne copy of aldA. Moreover, virtual and biological screening against the two proteins led to a set of compounds that inhibited the growth of E. coli and Salmonella enterica serovar Typhimurium synergistically at 100–200 μM individual concentrations. These results highlight the power of metabolic models to drive basic biological discovery and their potential use to discover new combination antibiotics.
synthetic lethality; antibiotic development; drug discovery; systems biology; metabolic reconstruction; bacterial metabolism; model-based drug target discovery; pathway gap filling
The Human Microbiome Project (HMP) is a global initiative undertaken to identify and characterize the collection of human-associated microorganisms at multiple anatomic sites (skin, mouth, nose, colon, vagina), and to determine how intra-individual and inter-individual alterations in the microbiome influence human health, immunity, and different disease states. In this review article, we summarize the key findings and applications of the HMP that may impact pharmacology and personalized therapeutics. We propose a microbiome cloud model, reflecting the temporal and spatial uncertainty of defining an individual's microbiome composition, with examples of how intra-individual variations (such as age and mode of delivery) shape the microbiome structure. Additionally, we discuss how this microbiome cloud concept explains the difficulty to define a core human microbiome and to classify individuals according to their biome types. Detailed examples are presented on microbiome changes related to colorectal cancer, antibiotic administration, and pharmacomicrobiomics, or drug–microbiome interactions, highlighting how an improved understanding of the human microbiome, and alterations thereof, may lead to the development of novel therapeutic agents, the modification of antibiotic policies and implementation, and improved health outcomes. Finally, the prospects of a collaborative computational microbiome research initiative in Africa are discussed.
Group A Streptococcus (GAS) is a leading cause of infection-related mortality in humans. All GAS serotypes express the Lancefield group A carbohydrate (GAC), comprising a polyrhamnose backbone with an immunodominant N-acetylglucosamine (GlcNAc) side chain, which is the basis of rapid diagnostic tests. No biological function has been attributed to this conserved antigen. Here we identify and characterize the GAC biosynthesis genes,gacA-L. An isogenic mutant of the glycosyltransferase gacI, which is defective for GlcNAcside chain addition, is attenuated for virulence in two infection models, in association with increased sensitivity to neutrophil killing, platelet-derived antimicrobials in serum and the cathelicidin antimicrobial peptide LL-37. Antibodies to GAC lacking the GlcNAc side chain and containing only polyrhamnose promoted opsonophagocytic killing of multiple GAS serotypes and protected against systemic GAS challenge after passive immunization. Thus, the Lancefield antigen plays a functional role in GAS pathogenesis and its understanding has implications for vaccine development.
Metagenomics, or sequencing of the genetic material from a complete microbial community, is a
promising tool to discover novel microbes and viruses. Viral metagenomes typically contain many
unknown sequences. Here we describe the discovery of a previously unidentified bacteriophage present
in the majority of published human faecal metagenomes, which we refer to as crAssphage. Its
~97 kbp genome is six times more abundant in publicly available metagenomes than all other
known phages together; it comprises up to 90% and 22% of all reads in virus-like particle
(VLP)-derived metagenomes and total community metagenomes, respectively; and it totals 1.68% of all
human faecal metagenomic sequencing reads in the public databases. The majority of
crAssphage-encoded proteins match no known sequences in the database, which is why it was not
detected before. Using a new co-occurrence profiling approach, we predict a Bacteroides host
for this phage, consistent with Bacteroides-related protein homologues and a unique
carbohydrate-binding domain encoded in the phage genome.
Metagenomic studies of microbial communities often report DNA sequences from
unidentified viruses. Here, Dutilh et al. analyse metagenomic data to reveal the complete
genome of an abundant, ubiquitous virus from human faeces, and predict that the virus infects
bacteria of the Bacteroides group.
Metagenomics, or sequencing of the genetic material from a complete microbial community, is a promising tool to discover novel microbes and viruses. Viral metagenomes typically contain many unknown sequences. Here we describe the discovery of a previously unidentified bacteriophage present in the majority of published human fecal metagenomes, which we refer to as crAssphage. Its ~97 kbp genome is six times more abundant in publicly available metagenomes than all other known phages together; comprises up to 90% and 22% of all reads in virus-like particle (VLP)-derived metagenomes and total community metagenomes, respectively; and totals 1.68% of all human fecal metagenomic sequencing reads in the public databases. The majority of crAssphage-encoded proteins match no known sequences in the database, which is why it was not detected before. Using a new co-occurrence profiling approach, we predict a Bacteroides host for this phage, consistent with Bacteroides-related protein homologs and a unique carbohydrate-binding domain encoded in the phage genome,.
Human virome; biological dark matter; metagenome assembly; phage-host prediction; depth profiles
Background: Serotype M4 group A Streptococcus lack hyaluronic acid (HA) capsule, but are capable of causing human disease.
Results: Encapsulation was achieved by introducing the hasABC capsule synthesis operon in the absence of HA-degrading enzyme hyaluronate lyase (HylA).
Conclusion: Capsule expression does not enhance M4 GAS virulence.
Significance: We demonstrate a mutually exclusive interaction between GAS capsule and HylA expression.
A recent analysis of group A Streptococcus (GAS) invasive infections in Australia has shown a predominance of M4 GAS, a serotype recently reported to lack the antiphagocytic hyaluronic acid (HA) capsule. Here, we use molecular genetics and bioinformatics techniques to characterize 17 clinical M4 isolates associated with invasive disease in children during this recent epidemiology. All M4 isolates lacked HA capsule, and whole genome sequence analysis of two isolates revealed the complete absence of the hasABC capsule biosynthesis operon. Conversely, M4 isolates possess a functional HA-degrading hyaluronate lyase (HylA) enzyme that is rendered nonfunctional in other GAS through a point mutation. Transformation with a plasmid expressing hasABC restored partial encapsulation in wild-type (WT) M4 GAS, and full encapsulation in an isogenic M4 mutant lacking HylA. However, partial encapsulation reduced binding to human complement regulatory protein C4BP, did not enhance survival in whole human blood, and did not increase virulence of WT M4 GAS in a mouse model of systemic infection. Bioinformatics analysis found no hasABC homologs in closely related species, suggesting that this operon was a recent acquisition. These data showcase a mutually exclusive interaction of HA capsule and active HylA among strains of this leading human pathogen.
Bacterial Pathogenesis; Hyaluronan; Hyaluronate; Infectious Disease; Streptococcus Pyogenes (S. Pyogenes); Group A Streptococcus; Hyaluronate Lyase; Hyaluronic acid Capsule; Invasive Disease; Nonencapsulated
Over the preceding years and to date, the definitive mode of human infection by Helicobacter pylori has remained largely unknown and has thus gained the interest of researchers around the world. Numerous studies investigated possible sources of transmission of this emerging carcinogenic pathogen that colonizes >50% of humans, in many of which contaminated water is mentioned as a major cause. The infection rate is especially higher in developing countries, where contaminated water, combined with social hardships and poor sanitary conditions, plays a key role. Judging from the growing global population and the changing climate, the rate is expected to rise. Here, we sum up the current views of the water transmission hypothesis, and we discuss its implications.
IMS, immunomagnetic separation; PCR, polymerase chain reaction; VBNC, viable-but-non-culturable; Epidemiology; Infectious diseases; Climate change; Water crisis
Group A Streptococcus (GAS) is a human-specific bacterial pathogen responsible for serious morbidity and mortality worldwide. The hyaluronic acid (HA) capsule of GAS is a major virulence factor, contributing to bloodstream survival through resistance to neutrophil and antimicrobial peptide killing and to in vivo pathogenicity. Capsule biosynthesis has been exclusively attributed to the ubiquitous hasABC hyaluronan synthase operon, which is highly conserved across GAS serotypes. Previous reports indicate that hasA, encoding hyaluronan synthase, and hasB, encoding UDP-glucose 6-dehydrogenase, are essential for capsule production in GAS. Here, we report that precise allelic exchange mutagenesis of hasB in GAS strain 5448, a representative of the globally disseminated M1T1 serotype, did not abolish HA capsule synthesis. In silico whole-genome screening identified a putative HasB paralog, designated HasB2, with 45% amino acid identity to HasB at a distant location in the GAS chromosome. In vitro enzymatic assays demonstrated that recombinant HasB2 is a functional UDP-glucose 6-dehydrogenase enzyme. Mutagenesis of hasB2 alone slightly decreased capsule abundance; however, a ΔhasB ΔhasB2 double mutant became completely acapsular. We conclude that HasB is not essential for M1T1 GAS capsule biogenesis due to the presence of a newly identified HasB paralog, HasB2, which most likely resulted from gene duplication. The identification of redundant UDP-glucose 6-dehydrogenases underscores the importance of HA capsule expression for M1T1 GAS pathogenicity and survival in the human host.
All sequence data contain inherent information that can be measured by Shannon's uncertainty theory. Such measurement is valuable in evaluating large data sets, such as metagenomic libraries, to prioritize their analysis and annotation, thus saving computational resources. Here, Shannon's index of complete phage and bacterial genomes was examined. The information content of a genome was found to be highly dependent on the genome length, GC content, and sequence word size. In metagenomic sequences, the amount of information correlated with the number of matches found by comparison to sequence databases. A sequence with more information (higher uncertainty) has a higher probability of being significantly similar to other sequences in the database. Measuring uncertainty may be used for rapid screening for sequences with matches in available database, prioritizing computational resources, and indicating which sequences with no known similarities are likely to be important for more detailed analysis.
The influence of resident gut microbes on xenobiotic metabolism has been investigated at different levels throughout the past five decades. However, with the advance in sequencing and pyrotagging technologies, addressing the influence of microbes on xenobiotics had to evolve from assessing direct metabolic effects on toxins and botanicals by conventional culture-based techniques to elucidating the role of community composition on drugs metabolic profiles through DNA sequence-based phylogeny and metagenomics. Following the completion of the Human Genome Project, the rapid, substantial growth of the Human Microbiome Project (HMP) opens new horizons for studying how microbiome compositional and functional variations affect drug action, fate, and toxicity (pharmacomicrobiomics), notably in the human gut. The HMP continues to characterize the microbial communities associated with the human gut, determine whether there is a common gut microbiome profile shared among healthy humans, and investigate the effect of its alterations on health. Here, we offer a glimpse into the known effects of the gut microbiota on xenobiotic metabolism, with emphasis on cases where microbiome variations lead to different therapeutic outcomes. We discuss a few examples representing how the microbiome interacts with human metabolic enzymes in the liver and intestine. In addition, we attempt to envisage a roadmap for the future implications of the HMP on therapeutics and personalized medicine.
Human microbiome project; Xenobitoics; Liver enzymes; Metagenome; Microbiota; Metabolomics; Metabonomics; Pharmacokinetics; Pharmacodynamics; Pharmacomicrobiomics
The remarkable advance in sequencing technology and the rising interest in medical and environmental microbiology, biotechnology, and synthetic biology resulted in a deluge of published microbial genomes. Yet, genome annotation, comparison, and modeling remain a major bottleneck to the translation of sequence information into biological knowledge, hence computational analysis tools are continuously being developed for rapid genome annotation and interpretation. Among the earliest, most comprehensive resources for prokaryotic genome analysis, the SEED project, initiated in 2003 as an integration of genomic data and analysis tools, now contains >5,000 complete genomes, a constantly updated set of curated annotations embodied in a large and growing collection of encoded subsystems, a derived set of protein families, and hundreds of genome-scale metabolic models. Until recently, however, maintaining current copies of the SEED code and data at remote locations has been a pressing issue. To allow high-performance remote access to the SEED database, we developed the SEED Servers (http://www.theseed.org/servers): four network-based servers intended to expose the data in the underlying relational database, support basic annotation services, offer programmatic access to the capabilities of the RAST annotation server, and provide access to a growing collection of metabolic models that support flux balance analysis. The SEED servers offer open access to regularly updated data, the ability to annotate prokaryotic genomes, the ability to create metabolic reconstructions and detailed models of metabolism, and access to hundreds of existing metabolic models. This work offers and supports a framework upon which other groups can build independent research efforts. Large integrations of genomic data represent one of the major intellectual resources driving research in biology, and programmatic access to the SEED data will provide significant utility to a broad collection of potential users.
PMID: 22523528 CAMSID: cams2043
Group A Streptococcus (GAS) causes rare but life-threatening syndromes of necrotizing fasciitis and toxic shock-like syndrome in humans. The GAS serotype M1T1 clone has globally disseminated, and mutations in the control of virulence regulatory sensor kinase (covRS) operon correlate with severe invasive disease. Here, a cohort of non-M1 GAS was screened to determine whether mutation in covRS triggers systemic dissemination in divergent M serotypes. A GAS disease model defining parameters governing invasive propensity of differing M types is proposed. The vast majority of GAS infection is benign. Nonetheless, many divergent M types possess limited capacity to cause invasive infection. M1T1 GAS readily switch to a covRS mutant form that is neutrophil resistant and frequently associated with systemic infection. Whilst non-M1 GAS are shown in this study to less frequently accumulate covRS mutations in vivo, such mutants are isolated from invasive infections and exhibit neutrophil resistance and enhanced virulence. The reduced capacity of non-M1 GAS to switch to the hypervirulent covRS mutant form provides an explanation for the comparatively less frequent isolation of non-M1 serotypes from invasive human infections.
Animal models; Bacteriology; Immunity; Innate; Neutrophils; Streptococcus; Virulence factors; Invasive infection
The aquatic zoonotic pathogen Streptococcus iniae represents a threat to the worldwide aquaculture industry and poses a risk to humans who handle raw fish. Because little is known about the mechanisms of S. iniae pathogenesis or virulence factors, we established a high-throughput system combining whole-genome pyrosequencing and transposon mutagenesis that allowed us to identify virulence proteins, including Pdi, the polysaccharide deacetylase of S. iniae, that we describe here. Using bioinformatics tools, we identified a highly conserved signature motif in Pdi that is also conserved in the peptidoglycan deacetylase PgdA protein family. A Δpdi mutant was attenuated for virulence in the hybrid striped bass model and for survival in whole fish blood. Moreover, Pdi was found to promote bacterial resistance to lysozyme killing and the ability to adhere to and invade epithelial cells. On the other hand, there was no difference in the autolytic potential, resistance to oxidative killing or resistance to cationic antimicrobial peptides between S. iniae wild-type and Δpdi. In conclusion, we have demonstrated that pdi is involved in S. iniae adherence and invasion, lysozyme resistance and survival in fish blood, and have shown that pdi plays a role in the pathogenesis of S. iniae. Identification of Pdi and other S. iniae virulence proteins is a necessary initial step towards the development of appropriate preventive and therapeutic measures against diseases and economic losses caused by this pathogen.
The onset of infection and the switch from primary to secondary niches are dramatic environmental changes that not only alter bacterial transcriptional programs, but also perturb their sociomicrobiology, often driving minor subpopulations with mutant phenotypes to prevail in specific niches. Having previously reported that M1T1 Streptococcus pyogenes become hypervirulent in mice due to selection of mutants in the covRS regulatory genes, we set out to dissect the impact of these mutations in vitro and in vivo from the impact of other adaptive events. Using a murine subcutaneous chamber model to sample the bacteria prior to selection or expansion of mutants, we compared gene expression dynamics of wild type (WT) and previously isolated animal-passaged (AP) covS mutant bacteria both in vitro and in vivo, and we found extensive transcriptional alterations of pathoadaptive and metabolic gene sets associated with invasion, immune evasion, tissue-dissemination, and metabolic reprogramming. In contrast to the virulence-associated differences between WT and AP bacteria, Phenotype Microarray analysis showed minor in vitro phenotypic differences between the two isogenic variants. Additionally, our results reflect that WT bacteria's rapid host-adaptive transcriptional reprogramming was not sufficient for their survival, and they were outnumbered by hypervirulent covS mutants with SpeB−/Sdahigh phenotype, which survived up to 14 days in mice chambers. Our findings demonstrate the engagement of unique regulatory modules in niche adaptation, implicate a critical role for bacterial genetic heterogeneity that surpasses transcriptional in vivo adaptation, and portray the dynamics underlying the selection of hypervirulent covS mutants over their parental WT cells.