Development and Evaluation of Genome-Probing Microarrays for Monitoring Lactic Acid Bacteria

The genome-probing microarray (GPM) was developed for quantitative, high-throughput monitoring of community dynamics in lactic acid bacteria (LAB) fermentation through the deposit of 149 microbial genomes as probes on a glass slide. Compared to oligonucleotide microarrays, the specificity of GPM was remarkably increased to a species-specific level. GPM possesses about 10- to 100-fold higher sensitivity (2.5 ng of genomic DNA) than the currently used 50-mer oligonucleotide microarrays. Since signal variation between the different genomes was very low compared to that of cDNA or oligonucleotide-based microarrays, the capacity of global quantification of microbial genomes could also be observed in GPM hybridization. In order to assess the applicability of GPMs, LAB community dynamics were monitored during the fermentation of kimchi, a traditional Korean food. In this work, approximately 100 diverse LAB species could be quantitatively analyzed as actively involved in kimchi fermentation.     

Development and evaluation of genome-probing microarrays for monitoring lactic acid bacteria

The genome-probing microarray (GPM) was developed for quantitative, high-throughput monitoring of community dynamics in lactic acid bacteria (LAB) fermentation through the deposit of 149 microbial genomes as probes on a glass slide. Compared to oligonucleotide microarrays, the specificity of GPM was remarkably increased to a species-specific level. GPM possesses about 10- to 100-fold higher sensitivity (2.5 ng of genomic DNA) than the currently used 50-mer oligonucleotide microarrays. Since signal variation between the different genomes was very low compared to that of cDNA or oligonucleotide-based microarrays, the capacity of global quantification of microbial genomes could also be observed in GPM hybridization. In order to assess the applicability of GPMs, LAB community dynamics were monitored during the fermentation of kimchi, a traditional Korean food. In this work, approximately 100 diverse LAB species could be quantitatively analyzed as actively involved in kimchi fermentation.     

Exploring environmental intra-species diversity through non-redundant pangenome assemblies

At the genome level, microorganisms are highly adaptable both in terms of allele and gene composition. Such heritable traits emerge in response to different environmental niches and can have a profound influence on microbial community dynamics. As a consequence, any individual genome or population will contain merely a fraction of the total genetic diversity of any operationally defined “species”, whose ecological potential can thus be only fully understood by studying all of their genomes and the genes therein. This concept, known as the pangenome, is valuable for studying microbial ecology and evolution, as it partitions genomes into core (present in all the genomes from a species, and responsible for housekeeping and species-level niche adaptation among others) and accessory regions (present only in some, and responsible for intra-species differentiation). Here we present SuperPang, an algorithm producing pangenome assemblies from a set of input genomes of varying quality, including metagenome-assembled genomes (MAGs). SuperPang runs in linear time and its results are complete, non-redundant, preserve gene ordering and contain both coding and non-coding regions. Our approach provides a modular view of the pangenome, identifying operons and genomic islands, and allowing to track their prevalence in different populations. We illustrate this by analysing intra-species diversity in Polynucleobacter, a bacterial genus ubiquitous in freshwater ecosystems, characterized by their streamlined genomes and their ecological versatility. We show how SuperPang facilitates the simultaneous analysis of allelic and gene content variation under different environmental pressures, allowing us to study the drivers of microbial diversification at unprecedented resolution.     

Strain/species identification in metagenomes using genome-specific markers

Shotgun metagenome sequencing has become a fast, cheap and high-throughput technology for characterizing microbial communities in complex environments and human body sites. However, accurate identification of microorganisms at the strain/species level remains extremely challenging. We present a novel k-mer-based approach, termed GSMer, that identifies genome-specific markers (GSMs) from currently sequenced microbial genomes, which were then used for strain/species-level identification in metagenomes. Using 5390 sequenced microbial genomes, 8 770 321 50-mer strain-specific and 11 736 360 species-specific GSMs were identified for 4088 strains and 2005 species (4933 strains), respectively. The GSMs were first evaluated against mock community metagenomes, recently sequenced genomes and real metagenomes from different body sites, suggesting that the identified GSMs were specific to their targeting genomes. Sensitivity evaluation against synthetic metagenomes with different coverage suggested that 50 GSMs per strain were sufficient to identify most microbial strains with ≥0.25× coverage, and 10% of selected GSMs in a database should be detected for confident positive callings. Application of GSMs identified 45 and 74 microbial strains/species significantly associated with type 2 diabetes patients and obese/lean individuals from corresponding gastrointestinal tract metagenomes, respectively. Our result agreed with previous studies but provided strain-level information. The approach can be directly applied to identify microbial strains/species from raw metagenomes, without the effort of complex data pre-processing.     

The Sorcerer II Global Ocean Sampling Expedition: metagenomic characterization of viruses within aquatic microbial samples

Viruses are the most abundant biological entities on our planet. Interactions between viruses and their hosts impact several important biological processes in the world's oceans such as horizontal gene transfer, microbial diversity and biogeochemical cycling. Interrogation of microbial metagenomic sequence data collected as part of the Sorcerer II Global Ocean Expedition (GOS) revealed a high abundance of viral sequences, representing approximately 3% of the total predicted proteins. Cluster analyses of the viral sequences revealed hundreds to thousands of viral genes encoding various metabolic and cellular functions. Quantitative analyses of viral genes of host origin performed on the viral fraction of aquatic samples confirmed the viral nature of these sequences and suggested that significant portions of aquatic viral communities behave as reservoirs of such genetic material. Distributional and phylogenetic analyses of these host-derived viral sequences also suggested that viral acquisition of environmentally relevant genes of host origin is a more abundant and widespread phenomenon than previously appreciated. The predominant viral sequences identified within microbial fractions originated from tailed bacteriophages and exhibited varying global distributions according to viral family. Recruitment of GOS viral sequence fragments against 27 complete aquatic viral genomes revealed that only one reference bacteriophage genome was highly abundant and was closely related, but not identical, to the cyanomyovirus P-SSM4. The co-distribution across all sampling sites of P-SSM4-like sequences with the dominant ecotype of its host, Prochlorococcus supports the classification of the viral sequences as P-SSM4-like and suggests that this virus may influence the abundance, distribution and diversity of one of the most dominant components of picophytoplankton in oligotrophic oceans. In summary, the abundance and broad geographical distribution of viral sequences within microbial fractions, the prevalence of genes among viral sequences that encode microbial physiological function and their distinct phylogenetic distribution lend strong support to the notion that viral-mediated gene acquisition is a common and ongoing mechanism for generating microbial diversity in the marine environment.     

Searching for fat tails in CRISPR-Cas systems: Data analysis and mathematical modeling

Understanding CRISPR-Cas systems—the adaptive defence mechanism that about half of bacterial species and most of archaea use to neutralise viral attacks—is important for explaining the biodiversity observed in the microbial world as well as for editing animal and plant genomes effectively. The CRISPR-Cas system learns from previous viral infections and integrates small pieces from phage genomes called spacers into the microbial genome. The resulting library of spacers collected in CRISPR arrays is then compared with the DNA of potential invaders. One of the most intriguing and least well understood questions about CRISPR-Cas systems is the distribution of spacers across the microbial population. Here, using empirical data, we show that the global distribution of spacer numbers in CRISPR arrays across multiple biomes worldwide typically exhibits scale-invariant power law behaviour, and the standard deviation is greater than the sample mean. We develop a mathematical model of spacer loss and acquisition dynamics which fits observed data from almost four thousand metagenomes well. In analogy to the classical ‘rich-get-richer’ mechanism of power law emergence, the rate of spacer acquisition is proportional to the CRISPR array size, which allows a small proportion of CRISPRs within the population to possess a significant number of spacers. Our study provides an alternative explanation for the rarity of all-resistant super microbes in nature and why proliferation of phages can be highly successful despite the effectiveness of CRISPR-Cas systems.     

Genetic comparison of Bacillus anthracis and its close relatives using amplified fragment length polymorphism and polymerase chain reaction analysis

Amplified fragment length polymorphism (AFLP) analysis allows a rapid, relatively simple analysis of a large portion of a microbial genome, providing information about the species and its phylogenetic relationship to other microbes (Vos et al. 1995). The method simply surveys the genome for length and sequence polymorphisms. The AFLP pattern identified can be used for comparison to the genomes of other species. Unlike other methods, it does not rely on analysis of a single genetic locus that may bias the interpretation of results and does not require any prior knowledge of the targeted organism. Moreover, a standard set of reagents can be applied to any species without using species-specific information or molecular probes. We are using AFLP analysis to rapidly identify different bacterial species. A comparison of AFLP profiles generated from a large battery of Bacillus anthracis strains shows very little variability among different isolates (Keim et al. 1997). By contrast, there is a significant difference between AFLP profiles generated for any B. anthracis strain and even the most closely related Bacillus species. Sufficient variability is apparent among all known microbial species to allow phylogenetic analysis based on large numbers of genetically unlinked loci. These striking differences among AFLP profiles allow unambiguous identification of previously identified species and phylogenetic placement of newly characterized isolates relative to known species based on a large number of independent genetic loci. Data generated thus far show that the method provides phylogenetic analyses that are consistent with other widely accepted phylogenetic methods. However, AFLP analysis provides a more detailed analysis of the targets and samples a much larger portion of the genome. Consequently, it provides an inexpensive, rapid means of characterizing microbial isolates to further differentiate among strains and closely related microbial species. Such information cannot be rapidly generated by other means. AFLP sample analysis quickly generates a very large amount of molecular information about microbial genomes. However, this information cannot be analysed rapidly using manual methods. We are developing a large archive of electronic AFLP signatures that is being used to identify isolates collected from medical, veterinary, forensic and environmental samples. We are also developing the computational packages necessary to rapidly and unambiguously analyse the AFLP profiles and conduct a phylogenetic comparison of these data relative to information already in our database. We will use this archive and the associated algorithms to determine the species identity of previously uncharacterized isolates and place them phylogenetically relative to other microbes based on their AFLP signatures. This study provides significant new information about microbes with environmental, veterinary and medical significance. This information can be used in further studies to understand the relationships among these species and the factors that distinguish them from one another. It should also allow the identification of unique factors that contribute to important microbial traits, including pathogenicity and virulence. We are also using AFLP data to identify, isolate and sequence DNA fragments that are unique to particular microbial species and strains. The fragment patterns and sequence information provide insights into the complexity and organization of bacterial genomes relative to one another. They also provide the information necessary for the development of species-specific polymerase chain reaction primers that can be used to interrogate complex samples for the presence of B. anthracis, other microbial pathogens or their remnants.     

Reconstructing genome trees of prokaryotes using overlapping genes

Background  

Overlapping genes (OGs) are defined as adjacent genes whose coding sequences overlap partially or entirely. In fact, they are ubiquitous in microbial genomes and more conserved between species than non-overlapping genes. Based on this property, we have previously implemented a web server, named OGtree, that allows the user to reconstruct genome trees of some prokaryotes according to their pairwise OG distances. By analogy to the analyses of gene content and gene order, the OG distance between two genomes we defined was based on a measure of combining OG content (i.e., the normalized number of shared orthologous OG pairs) and OG order (i.e., the normalized OG breakpoint distance) in their whole genomes. A shortcoming of using the concept of breakpoints to define the OG distance is its inability to analyze the OG distance of multi-chromosomal genomes. In addition, the amount of overlapping coding sequences between some distantly related prokaryotic genomes may be limited so that it is hard to find enough OGs to properly evaluate their pairwise OG distances.     

En route to a genome-based classification of Archaea and Bacteria?

Given the considerable promise whole-genome sequencing offers for phylogeny and classification, it is surprising that microbial systematics and genomics have not yet been reconciled. This might be due to the intrinsic difficulties in inferring reasonable phylogenies from genomic sequences, particularly in the light of the significant amount of lateral gene transfer in prokaryotic genomes. However, recent studies indicate that the species tree and the hierarchical classification based on it are still meaningful concepts, and that state-of-the-art phylogenetic inference methods are able to provide reliable estimates of the species tree to the benefit of taxonomy. Conversely, we suspect that the current lack of completely sequenced genomes for many of the major lineages of prokaryotes and for most type strains is a major obstacle in progress towards a genome-based classification of microorganisms. We conclude that phylogeny-driven microbial genome sequencing projects such as the Genomic Encyclopaedia of Archaea and Bacteria (GEBA) project are likely to rectify this situation.     

Symbiont genomics,our new tangled bank

Microbial symbionts inhabit the soma and surfaces of most multicellular species and instigate both beneficial and harmful infections. Despite their ubiquity, we are only beginning to resolve major patterns of symbiont ecology and evolution. Here, we summarize the history, current progress, and projected future of the study of microbial symbiont evolution throughout the tree of life. We focus on the recent surge of data that whole-genome sequencing has introduced into the field, in particular the links that are now being made between symbiotic lifestyle and molecular evolution. Post-genomic and systems biology approaches are also emerging as powerful techniques to investigate host–microbe interactions, both at the molecular level of the species interface and at the global scale. In parallel, next-generation sequencing technologies are allowing new questions to be addressed by providing access to population genomic data, as well as the much larger genomes of microbial eukaryotic symbionts and hosts. Throughout we describe the questions that these techniques are tackling and we conclude by listing a series of unanswered questions in microbial symbiosis that can potentially be addressed with the new technologies.     

Expanding our Understanding of Sequence-Function Relationships of Type II Polyketide Biosynthetic Gene Clusters: Bioinformatics-Guided Identification of Frankiamicin A from Frankia sp. EAN1pec

A large and rapidly increasing number of unstudied “orphan” natural product biosynthetic gene clusters are being uncovered in sequenced microbial genomes. An important goal of modern natural products research is to be able to accurately predict natural product structures and biosynthetic pathways from these gene cluster sequences. This requires both development of bioinformatic methods for global analysis of these gene clusters and experimental characterization of select products produced by gene clusters with divergent sequence characteristics. Here, we conduct global bioinformatic analysis of all available type II polyketide gene cluster sequences and identify a conserved set of gene clusters with unique ketosynthase α/β sequence characteristics in the genomes of Frankia species, a group of Actinobacteria with underexploited natural product biosynthetic potential. Through LC-MS profiling of extracts from several Frankia species grown under various conditions, we identified Frankia sp. EAN1pec as producing a compound with spectral characteristics consistent with the type II polyketide produced by this gene cluster. We isolated the compound, a pentangular polyketide which we named frankiamicin A, and elucidated its structure by NMR and labeled precursor feeding. We also propose biosynthetic and regulatory pathways for frankiamicin A based on comparative genomic analysis and literature precedent, and conduct bioactivity assays of the compound. Our findings provide new information linking this set of Frankia gene clusters with the compound they produce, and our approach has implications for accurate functional prediction of the many other type II polyketide clusters present in bacterial genomes.     

Subspecies in the global human gut microbiome

Population genomics of prokaryotes has been studied in depth in only a small number of primarily pathogenic bacteria, as genome sequences of isolates of diverse origin are lacking for most species. Here, we conducted a large‐scale survey of population structure in prevalent human gut microbial species, sampled from their natural environment, with a culture‐independent metagenomic approach. We examined the variation landscape of 71 species in 2,144 human fecal metagenomes and found that in 44 of these, accounting for 72% of the total assigned microbial abundance, single‐nucleotide variation clearly indicates the existence of sub‐populations (here termed subspecies). A single subspecies (per species) usually dominates within each host, as expected from ecological theory. At the global scale, geographic distributions of subspecies differ between phyla, with Firmicutes subspecies being significantly more geographically restricted. To investigate the functional significance of the delineated subspecies, we identified genes that consistently distinguish them in a manner that is independent of reference genomes. We further associated these subspecies‐specific genes with properties of the microbial community and the host. For example, two of the three Eubacterium rectale subspecies consistently harbor an accessory pro‐inflammatory flagellum operon that is associated with lower gut community diversity, higher host BMI, and higher blood fasting insulin levels. Using an additional 676 human oral samples, we further demonstrate the existence of niche specialized subspecies in the different parts of the oral cavity. Taken together, we provide evidence for subspecies in the majority of abundant gut prokaryotes, leading to a better functional and ecological understanding of the human gut microbiome in conjunction with its host.     

Genome diversity in microbial eukaryotes

The genomic peculiarities among microbial eukaryotes challenge the conventional wisdom of genome evolution. Currently, many studies and textbooks explore principles of genome evolution from a limited number of eukaryotic lineages, focusing often on only a few representative species of plants, animals and fungi. Increasing emphasis on studies of genomes in microbial eukaryotes has and will continue to uncover features that are either not present in the representative species (e.g. hypervariable karyotypes or highly fragmented mitochondrial genomes) or are exaggerated in microbial groups (e.g. chromosomal processing between germline and somatic nuclei). Data for microbial eukaryotes have emerged from recent genome sequencing projects, enabling comparisons of the genomes from diverse lineages across the eukaryotic phylogenetic tree. Some of these features, including amplified rDNAs, subtelomeric rDNAs and reduced genomes, appear to have evolved multiple times within eukaryotes, whereas other features, such as absolute strand polarity, are found only within single lineages.     

Mapping in plants: progress and prospects

Comprehensive genetic maps are now available for all of the world's important crop species. Data show a remarkable conservation of order of markers over family-wide taxonomic groupings and illuminate species relationships and mechanisms of genome evolution. Comparison of genetic and physical maps has revealed differences in genetic distance throughout genomes with implications for genome organization, gene isolation and transformation.     

Standard operating procedure for computing pangenome trees

We present the pan-genome tree as a tool for visualizing similarities and differences between closely related microbial genomes within a species or genus. Distance between genomes is computed as a weighted relative Manhattan distance based on gene family presence/absence. The weights can be chosen with emphasis on groups of gene families conserved to various degrees inside the pan-genome. The software is available for free as an R-package.     

Accurate genome relative abundance estimation based on shotgun metagenomic reads

Accurate estimation of microbial community composition based on metagenomic sequencing data is fundamental for subsequent metagenomics analysis. Prevalent estimation methods are mainly based on directly summarizing alignment results or its variants; often result in biased and/or unstable estimates. We have developed a unified probabilistic framework (named GRAMMy) by explicitly modeling read assignment ambiguities, genome size biases and read distributions along the genomes. Maximum likelihood method is employed to compute Genome Relative Abundance of microbial communities using the Mixture Model theory (GRAMMy). GRAMMy has been demonstrated to give estimates that are accurate and robust across both simulated and real read benchmark datasets. We applied GRAMMy to a collection of 34 metagenomic read sets from four metagenomics projects and identified 99 frequent species (minimally 0.5% abundant in at least 50% of the data-sets) in the human gut samples. Our results show substantial improvements over previous studies, such as adjusting the over-estimated abundance for Bacteroides species for human gut samples, by providing a new reference-based strategy for metagenomic sample comparisons. GRAMMy can be used flexibly with many read assignment tools (mapping, alignment or composition-based) even with low-sensitivity mapping results from huge short-read datasets. It will be increasingly useful as an accurate and robust tool for abundance estimation with the growing size of read sets and the expanding database of reference genomes.     

Microbial systematics in the post-genomics era

Microbial systematics and phylogeny should form the foundation and guiding light for a comprehensive understanding of different aspects of microbiology. However, there are many critical issues in microbial systematics that are currently not resolved. Some of these include: how to define and delimit a prokaryotic species; development of rationale criteria for the assignment of higher taxonomic ranks; understanding what unique properties distinguish species from different groups; and understanding the branching order and interrelationship among higher prokaryotic clades. The sequencing of genomes from large numbers of cultured as well as uncultured microbes covering prokaryotic diversity provides unique means to achieve these important objectives. Prokaryotic genomes are found to be very diverse and dynamic and horizontal gene transfers (HGTs) are indicated to have played important role in species/genome evolution. Although HGT adds a layer of complexity in terms of understanding the genomes and species evolution, it is contended that vast majority of genes and genetic characteristics that are distinctive characteristics of higher prokaryotic taxa are vertically inherited and based on them a solid foundation for microbial systematics can be developed. We describe two kinds of molecular markers consisting of conserved indels in protein sequences and whole proteins that are specific for different groups that are proving particularly valuable in defining different prokaryotic groups in clear molecular terms and in understanding their interrelationships. The genetic and biochemical studies on these taxa-specific molecular markers also open the way to discover novel biochemical and physiological characteristics that are unique properties of these groups.     

Four basic symmetry types in the universal 7-cluster structure of microbial genomic sequences

Coding information is the main source of heterogeneity (non-randomness) in the sequences of microbial genomes. The heterogeneity corresponds to a cluster structure in triplet distributions of relatively short genomic fragments (200-400 bp). We found a universal 7-cluster structure in microbial genomic sequences and explained its properties. We show that codon usage of bacterial genomes is a multi-linear function of their genomic G+C-content with high accuracy. Based on the analysis of 143 completely sequenced bacterial genomes available in Genbank in August 2004, we show that there are four "pure" types of the 7-cluster structure observed. All 143 cluster animated 3D-scatters are collected in a database which is made available on our web-site (http://www.ihes.fr/~zinovyev/7clusters). The findings can be readily introduced into software for gene prediction, sequence alignment or microbial genomes classification.     

Systematics and emerging infectious diseases: from management to solution

The crisis of emerging infectious disease stems from the absence of comprehensive taxonomic inventories of the world's parasites, which includes the world's pathogens. Recent technological developments raise hopes that the global inventory of species, including potential pathogens, can be accomplished in a timely and cost-effective manner. The phylogenetics revolution initiated by systematists provides a means by which information about pathogen transmission dynamics can be placed in a predictive framework. Increasingly, that information is widely available in digital form on the Internet. Systematic biology is well positioned to play a crucial role in efforts to be proactive in the arena of emerging parasitic and infectious diseases.     

基于微生物共培养的隐性基因簇激活策略

微生物次级代谢产物是药物先导化合物的重要源泉之一。随着测序技术的迅猛发展,越来越多的微生物基因组得以测序完成。伴随着测序技术的进步,生物信息学也得到了快速发展。基因组序列分析发现,链霉菌和丝状真菌等微生物中存在大量的已知的或未知的次级代谢物生物合成基因簇(secondary metabolite-biosynthetic gene clusters,SM-BGCs)。然而,在实验室培养条件下大部分基因簇无法表达或表达量很低,导致难以发现这些基因簇所对应的代谢产物,人们将这类基因簇称为“隐性基因簇”或“沉默基因簇”。通过调节基因簇中特异调控基因或基因簇外全局性调控基因的表达,对代谢途径的定向改造,以及将基因簇导入异源宿主等策略,能够激活部分隐性基因簇的表达。通过激活隐性基因簇的表达,能够发现通过常规实验室培养无法获得的具有独特生物活性的新结构代谢产物,成为创新药物的重要来源之一。然而,这些基因簇激活策略都严重依赖于对特定菌株或宿主的遗传操作。近年来,通过模拟自然混合培养中微生物间相互作用,开发了通过混合特定微生物菌株在厌氧或好氧条件下激活隐性基因簇的方法,称之为共培养激活策略。这种策略不依赖于基因组信息,也不依赖于对特定菌株或宿主的遗传操作技术,具有操作简单和方便的优点。共培养策略需要混合培养的不同微生物具有相似的生长速度以及不能够产生拮抗等要求,因而也部分限制了该策略的应用。近期合成微生物组学的出现有可能改变这一限制,使共培养策略得到更加广泛的应用。本文围绕微生物共培养体系和应用、基于共培养策略的产物挖掘以及可能的激活机制等进行了综述。