Microbiology in the post-genomic era

A generic approach to infer community-level fitness of microbial genes

The gene content in a metagenomic pool defines the function potential of a microbial community. Natural selection, operating on the level of genomes or genes, shapes the evolution of community functions by enriching some genes while depriving the others. Despite the importance of microbiomes in the environment and health, a general metric to evaluate the community-wide fitness of microbial genes remains lacking. In this work, we adapt the classic neutral model of species and use it to predict how the abundances of different genes will be shaped by selection, regardless of at which level the selection acts. We establish a simple metric that quantitatively infers the average survival capability of each gene in a microbiome. We then experimentally validate the predictions using synthetic communities of barcoded Escherichia coli strains undergoing neutral assembly and competition. We further show that this approach can be applied to publicly available metagenomic datasets to gain insights into the environment-function interplay of natural microbiomes.

Microbiome single cell atlases generated with a commercial instrument

Single cell sequencing is useful for resolving complex systems into their composite cell types and computationally mining them for unique features that are masked in pooled sequencing. However, while commercial instruments have made single cell analysis widespread for mammalian cells, analogous tools for microbes are limited. Here, we present EASi-seq (Easily Accessible Single microbe sequencing). By adapting the single cell workflow of the commercial Mission Bio Tapestri instrument, this method allows for efficient sequencing of individual microbes' genomes. EASi-seq allows thousands of microbes to be sequenced per run and, as we show, can generate detailed atlases of human and environmental microbiomes. The ability to capture large shotgun genome datasets from thousands of single microbes provides new opportunities in discovering and analyzing species subpopulations. To facilitate this, we develop a companion bioinformatic pipeline that clusters microbes by similarity, improving whole genome assembly, strain identification, taxonomic classification, and gene annotation. In addition, we demonstrate integration of metagenomic contigs with the EASi-seq datasets to reduce capture bias and increase coverage. Overall, EASi-seq enables high quality single cell genomic data for microbiome samples using an accessible workflow that can be run on a commercially available platform.

Involvement of the Gut Microbiome in the Local and Systemic Immune Response to Pancreatic Ductal Adenocarcinoma

The systemic and local immunosuppression exhibited by pancreatic ductal adenocarcinoma (PDAC) contributes significantly to its aggressive nature. There is a need for a greater understanding of the mechanisms behind this profound immune evasion, which makes it one of the most challenging malignancies to treat and thus one of the leading causes of cancer death worldwide. The gut microbiome is now thought to be the largest immune organ in the body and has been shown to play an important role in multiple immune-mediated diseases. By summarizing the current literature, this review examines the mechanisms by which the gut microbiome may modulate the immune response to PDAC. Evidence suggests that the gut microbiome can alter immune cell populations both in the peripheral blood and within the tumour itself in PDAC patients. In addition, evidence suggests that the gut microbiome influences the composition of the PDAC tumour microbiome, which exerts a local effect on PDAC tumour immune infiltration. Put together, this promotes the gut microbiome as a promising route for future therapies to improve immune responses in PDAC patients.

Pancreatic Exocrine Insufficiency and the Gut Microbiome in Pancreatic Cancer: A Target for Future Diagnostic Tests and Therapies?

Pancreatic exocrine insufficiency (PEI) is common amongst pancreatic cancer patients and is associated with poorer treatment outcomes. Pancreatic enzyme replacement therapy (PERT) is known to improve outcomes in pancreatic cancer, but the mechanisms are not fully understood. The aim of this narrative literature review is to summarise the current evidence linking PEI with microbiome dysbiosis, assess how microbiome composition may be impacted by PERT treatment, and look towards possible future diagnostic and therapeutic targets in this area. Early evidence in the literature reveals that there are complex mechanisms by which pancreatic secretions modulate the gut microbiome, so when these are disturbed, as in PEI, gut microbiome dysbiosis occurs. PERT has been shown to return the gut microbiome towards normal, so called rebiosis, in animal studies. Gut microbiome dysbiosis has multiple downstream effects in pancreatic cancer such as modulation of the immune response and the response to chemotherapeutic agents. It therefore represents a possible future target for future therapies. In conclusion, it is likely that the gut microbiome of pancreatic cancer patients with PEI exhibits dysbiosis and that this may potentially be reversible with PERT. However, further human studies are required to determine if this is indeed the case.

Diversifying the concept of model organisms in the age of -omics

In today's post-genomic era, it is crucial to rethink the concept of model organisms. While a few historically well-established organisms, e.g. laboratory rodents, have enabled significant scientific breakthroughs, there is now a pressing need for broader inclusion. Indeed, new organisms and models, from complex microbial communities to holobionts, are essential to fully grasp the complexity of biological principles across the breadth of biodiversity. By fostering collaboration between biology, advanced molecular science and omics communities, we can collectively adopt new models, unraveling their molecular functioning, and uncovering fundamental mechanisms. This concerted effort will undoubtedly enhance human health, environmental quality, and biodiversity conservation.

Revolutionizing Medical Microbiology: How Molecular and Genomic Approaches Are Changing Diagnostic Techniques

Molecular and genomic approaches have revolutionized medical microbiology by offering faster and more accurate diagnostic techniques for infectious diseases. Traditional methods, which include culturing microbes and biochemical testing, are time-consuming and may not detect antibiotic-resistant strains. In contrast, molecular and genomic methods, including polymerase chain reaction (PCR)-based techniques and whole-genome sequencing, provide rapid and precise detection of pathogens, early-stage diseases, and antibiotic-resistant strains. These approaches have advantages such as high sensitivity and specificity, the potential for targeted therapies, and personalized medicine. However, implementing molecular and genomic techniques faces challenges related to cost, equipment, expertise, and data analysis. Ethical and legal considerations regarding patient privacy and genetic data usage also arise. Nonetheless, the future of medical microbiology lies in the widespread adoption of molecular and genomic approaches, which can lead to improved patient outcomes and the identification of antibiotic-resistant strains. Continued advancements, education, and exploration of ethical implications are necessary to fully harness the potential of molecular and genomic techniques in medical microbiology.

Human Listeriosis

Listeria monocytogenes is a Gram-positive facultative intracellular pathogen that can cause severe invasive infections upon ingestion with contaminated food. Clinically, listerial disease, or listeriosis, most often presents as bacteremia, meningitis or meningoencephalitis, and pregnancy-associated infections manifesting as miscarriage or neonatal sepsis. Invasive listeriosis is life-threatening and a main cause of foodborne illness leading to hospital admissions in Western countries. Sources of contamination can be identified through international surveillance systems for foodborne bacteria and strains' genetic data sharing. Large-scale whole genome studies have increased our knowledge on the diversity and evolution of L. monocytogenes, while recent pathophysiological investigations have improved our mechanistic understanding of listeriosis. In this article, we present an overview of human listeriosis with particular focus on relevant features of the causative bacterium, epidemiology, risk groups, pathogenesis, clinical manifestations, and treatment and prevention.

G-SAIP: Graphical Sequence Alignment Through Parallel Programming in the Post-Genomic Era

A common task in bioinformatics is to compare DNA sequences to identify similarities between organisms at the sequence level. An approach to such comparison is the dot-plots, a 2-dimensional graphical representation to analyze DNA or protein alignments. Dot-plots alignment software existed before the sequencing revolution, and now there is an ongoing limitation when dealing with large-size sequences, resulting in very long execution times. High-Performance Computing (HPC) techniques have been successfully used in many applications to reduce computing times, but so far, very few applications for graphical sequence alignment using HPC have been reported. Here, we present G-SAIP (Graphical Sequence Alignment in Parallel), a software capable of spawning multiple distributed processes on CPUs, over a supercomputing infrastructure to speed up the execution time for dot-plot generation up to 1.68× compared with other current fastest tools, improve the efficiency for comparative structural genomic analysis, phylogenetics because the benefits of pairwise alignments for comparison between genomes, repetitive structure identification, and assembly quality checking.

proGenomes3: approaching one million accurately and consistently annotated high-quality prokaryotic genomes

The interpretation of genomic, transcriptomic and other microbial 'omics data is highly dependent on the availability of well-annotated genomes. As the number of publicly available microbial genomes continues to increase exponentially, the need for quality control and consistent annotation is becoming critical. We present proGenomes3, a database of 907 388 high-quality genomes containing 4 billion genes that passed stringent criteria and have been consistently annotated using multiple functional and taxonomic databases including mobile genetic elements and biosynthetic gene clusters. proGenomes3 encompasses 41 171 species-level clusters, defined based on universal single copy marker genes, for which pan-genomes and contextual habitat annotations are provided. The database is available at http://progenomes.embl.de/.

Genetic Features of Mycobacterium avium subsp. paratuberculosis Strains Circulating in the West of France Deciphered by Whole-Genome Sequencing

Paratuberculosis is a chronic infection of the intestine, mainly the ileum, caused by Mycobacterium avium subsp. paratuberculosis in cattle and other ruminants. This enzootic disease is present worldwide and has a negative impact on the dairy cattle industry. For this subspecies, the current genotyping tools do not provide the needed resolution to investigate the genetic diversity of closely related strains. These limitations can be overcome by the application of whole-genome sequencing (WGS), particularly for clonal populations such as M. avium subsp. paratuberculosis. The purpose of the present study was to undertake a WGS analysis with a panel of 200 animal field M. avium subsp. paratuberculosis strains selected based on a previous large-scale longitudinal study of Prim'Holstein and Normande dairy breeds naturally infected with M. avium subsp. paratuberculosis in the West of France. The pangenome analysis revealed that M. avium subsp. paratuberculosis has a closed pangenome. The phylogeny, based on alignment of 2,786 nonhomoplasic single nucleotide polymorphisms (SNPs), showed that the strain population is structured into three clades independently of the cattle breed or geographic distribution. The increased resolution of phylogeny obtained by WGS confirmed the homoplasic nature of the markers variable-number tandem repeat (VNTR) and short sequence repeat (SSR) used for M. avium subsp. paratuberculosis genotyping. These phylogenetic data also revealed independent introductions of the different genotypes in two main waves since at least 2003. WGS applied to this sampling demonstrated the presence of mixed infections in herds and at the individual animal level. Collectively, the phylogeny results inferred with French isolates compared to M. avium subsp. paratuberculosis isolates from around the world suggest introductions of M. avium subsp. paratuberculosis genotypes through the animal trade. Relationships between genetic traits and epidemiological data can now be investigated to better understand transmission dynamics of the disease. IMPORTANCE Mycobacterium avium subsp. paratuberculosis causes Johne's disease in ruminants, which is present worldwide and has significant negative impacts on the dairy cattle industry and animal welfare. Prevention and control of M. avium subsp. paratuberculosis infection are hampered by knowledge gaps in strain virulence, genotype distribution, and transmission dynamics. This work has revealed new insights into M. avium subsp. paratuberculosis strains currently circulating in western France and how they are related to strains circulating globally. We applied whole-genome sequencing (WGS) to obtain comprehensive information on genome evolution and discrimination of closely related strains. This approach revealed the history of M. avium subsp. paratuberculosis infection in France, refined the pangenomic characteristics of M. avium subsp. paratuberculosis, and demonstrated the existence of mixed infection in animals. Finally, this study identified predominant genotypes, which allow a better understanding of disease transmission dynamics. This information will facilitate tracking of this pathogen on farms and across agricultural regions, thus informing transmission pathways and disease control points.

Detection and Quantification of Antimicrobial-Resistant Cells in Aquatic Environments by Bioorthogonal Noncanonical Amino Acid Tagging

Aquatic environments are important reservoirs of antibiotic wastes, antibiotic resistance genes, and bacteria, enabling the persistence and proliferation of antibiotic resistance in different bacterial populations. To prevent the spread of antibiotic resistance, effective approaches to detect antimicrobial susceptibility in aquatic environments are highly desired. In this work, we adopt a metabolism-based bioorthogonal noncanonical amino acid tagging (BONCAT) method to detect, visualize, and quantify active antimicrobial-resistant bacteria in water samples by exploiting the differences in bacterial metabolic responses to antibiotics. The BONCAT approach can be applied to rapidly detect bacterial resistance to multiple antibiotics within 20 min of incubation, regardless of whether they act on proteins or DNA. In addition, the combination of BONCAT with the microscope enables the intuitive characterization of antibiotic-resistant bacteria in mixed systems at single-cell resolution. Furthermore, BONCAT coupled with flow cytometry exhibits good performance in determining bacterial resistance ratios to chloramphenicol and population heterogeneity in hospital wastewater samples. In addition, this approach is also effective in detecting antibiotic-resistant bacteria in natural water samples. Therefore, such a simple, fast, and efficient BONCAT-based approach will be valuable in monitoring the increase and spread of antibiotic resistance within natural and engineered aquatic environments.

Using unique ORFan genes as strain-specific identifiers for Escherichia coli

BACKGROUND

Bacterial identification at the strain level is a much-needed, but arduous and challenging task. This study aimed to develop a method for identifying and differentiating individual strains among multiple strains of the same bacterial species. The set used for testing the method consisted of 17 Escherichia coli strains picked from a collection of strains isolated in Germany, Spain, the United Kingdom and Vietnam from humans, cattle, swine, wild boars, and chickens. We targeted unique or rare ORFan genes to address the problem of selective and specific strain identification. These ORFan genes, exclusive to each strain, served as templates for developing strain-specific primers.

RESULTS

Most of the experimental strains (14 out of 17) possessed unique ORFan genes that were used to develop strain-specific primers. The remaining three strains were identified by combining a PCR for a rare gene with a selection step for isolating the experimental strains. Multiplex PCR allowed the successful identification of the strains both in vitro in spiked faecal material in addition to in vivo after experimental infections of pigs and recovery of bacteria from faecal material. In addition, primers for qPCR were also developed and quantitative readout from faecal samples after experimental infection was also possible.

CONCLUSIONS

The method described in this manuscript using strain-specific unique genes to identify single strains in a mixture of strains proved itself efficient and reliable in detecting and following individual strains both in vitro and in vivo, representing a fast and inexpensive alternative to more costly methods.

Clinical Application and Progress of Fecal Microbiota Transplantation in Liver Diseases: A Review

The human gut harbors a dense and highly diverse microbiota of approximately 1,000 bacterial species. The interaction between the host and gut bacteria strongly influences human health. Numerous evidence suggest that intestinal flora imbalance is closely associated with the development and treatment of liver diseases, including acute liver injury and chronic liver diseases (cirrhosis, autoimmune liver disease, and fatty liver). Therefore, regulating the gut microbiota is expected to be a new method for the adjuvant treatment of liver diseases. Fecal microbiota transplantation (FMT) is defined as the transplantation of gut microbiota from healthy donors to sick patients via the upper or lower gastrointestinal route to restore the normal intestinal balance. In this study, we briefly review the current research on the gut microbiota and its link to liver diseases and then summarize the evidence to elucidate the clinical application and development of FMT in liver disease treatment.

Microbial Communities in a Serpentinizing Aquifer Are Assembled through Strong Concurrent Dispersal Limitation and Selection

In recent years, our appreciation of the extent of habitable environments in Earth’s subsurface has greatly expanded, as has our understanding of the biodiversity contained within. Most studies have relied on single sampling points, rather than considering the long-term dynamics of subsurface environments and their microbial populations. One such habitat are aquifers associated with the aqueous alteration of ultramafic rocks through a process known as serpentinization. Ecological modeling performed on a multiyear time series of microbiology, hydrology, and geochemistry in an ultrabasic aquifer within the Coast Range Ophiolite reveals that community assembly is governed by undominated assembly (i.e., neither stochastic [random] nor deterministic [selective] processes alone govern assembly). Controls on community assembly were further assessed by characterizing aquifer hydrogeology and microbial community adaptations to the environment. These analyses show that low permeability rocks in the aquifer restrict the transmission of microbial populations between closely situated wells. Alpha and beta diversity measures and metagenomic and metatranscriptomic data from microbial communities indicate that high pH and low dissolved inorganic carbon levels impose strong environmental selection on microbial communities within individual wells. Here, we find that the interaction between strong selection imposed by extreme pH and enhanced ecological drift due to dispersal limitation imposed by slow fluid flow results in the undominated assembly signal observed throughout the site. Strong environmental selection paired with extremely low dispersal in the subsurface results in low diversity microbial communities that are well adapted to extreme pH conditions and subject to enhanced stochasticity introduced by ecological drift over time.

IMPORTANCE Microbial communities existing under extreme or stressful conditions have long been thought to be structured primarily by deterministic processes. The application of macroecology theory and modeling to microbial communities in recent years has spurred assessment of assembly processes in microbial communities, revealing that both stochastic and deterministic processes are at play to different extents within natural environments. We show that low diversity microbial communities in a hard-rock serpentinizing aquifer are assembled under the influence of strong selective processes imposed by high pH and enhanced ecological drift that occurs as the result of dispersal limitation due to the slow movement of water in the low permeability aquifer. This study demonstrates the important roles that both selection and dispersal limitation play in terrestrial serpentinites, where extreme pH assembles a microbial metacommunity well adapted to alkaline conditions and dispersal limitation drives compositional differences in microbial community composition between local communities in the subsurface.

Campylobacter coli isolated in Brazil typed by core genome Multilocus Sequence Typing shows high genomic diversity in a global context

Campylobacter has been one of the most common causative agent of bacterial food-borne gastroenteritis in humans worldwide. However, in Brazil the campylobacteriosis has been a neglected disease and there is insufficient data to estimate the incidence of this pathogen in the country.

AIMS

The current study aimed to determine the phylogenetic relationships among Campylobacter coli strains isolated in Brazil and to compare them with international Campylobacter isolates available in some public databases.

METHODS AND RESULTS

A total of 63C. coli strains isolated in Brazil were studied. The MLST analysis showed 18 different STs including three STs not yet described in the PubMLST database. The cgMLST allocated the Brazilian strains studied into five main clusters and each cluster comprised groups of strains with nearly identical cgMLST profiles and with significant genetic distance observed among the distinct clusters. The comparison of the Brazilian strains with 3401 isolates from different countries showed a wide distribution of these strains isolated in this country.

CONCLUSIONS

The results showed a high similarity among some strains studied and a wide distribution of the Brazilian strains when compared to isolates from different countries, which is an interesting data set since it showed a high genetic diversity of these strains from Brazil in a global context. This study contributed for a better genomic characterization of C. coli strains isolated in Brazil and provided important information about the diversity of this clinically-relevant pathogen.

Evolution of Microbial Genomics: Conceptual Shifts over a Quarter Century

Prokaryote genomics started in earnest in 1995, with the complete sequences of two small bacterial genomes, those of Haemophilus influenzae and Mycoplasma genitalium. During the next quarter century, the prokaryote genome database has been growing exponentially, with no saturation in sight. For most of these 25 years, genome sequencing remained limited to cultivable microbes. Together with next-generation sequencing methods, advances in metagenomics and single-cell genomics have lifted this limitation, providing for an increasingly unbiased characterization of the global prokaryote diversity. Advances in computational genomics followed the progress of genome sequencing, even if occasionally lagging behind. Several major new branches of bacteria and archaea were discovered, including Asgard archaea, the apparent closest relatives of eukaryotes and expansive groups of bacteria and archaea with small genomes thought to be symbionts of other prokaryotes. Comparative analysis of numerous prokaryote genomes spanning a wide range of evolutionary distances changed the conceptual foundations of microbiology, supplanting the notion of species genomes with fixed gene sets with that of dynamic pangenomes and the notion of a single Tree of Life (ToL) with a statistical tree-like trend among individual gene trees. Strides were also made towards a theory and quantitative laws of prokaryote genome evolution.

The Location of Substitutions and Bacterial Genome Arrangements

Increasing evidence supports the notion that different regions of a genome have unique rates of molecular change. This variation is particularly evident in bacterial genomes where previous studies have reported gene expression and essentiality tend to decrease, whereas substitution rates usually increase with increasing distance from the origin of replication. Genomic reorganization such as rearrangements occur frequently in bacteria and allow for the introduction and restructuring of genetic content, creating gradients of molecular traits along genomes. Here, we explore the interplay of these phenomena by mapping substitutions to the genomes of Escherichia coli, Bacillus subtilis, Streptomyces, and Sinorhizobium meliloti, quantifying how many substitutions have occurred at each position in the genome. Preceding work indicates that substitution rate significantly increases with distance from the origin. Using a larger sample size and accounting for genome rearrangements through ancestral reconstruction, our analysis demonstrates that the correlation between the number of substitutions and the distance from the origin of replication is significant but small and inconsistent in direction. Some replicons had a significantly decreasing trend (E. coli and the chromosome of S. meliloti), whereas others showed the opposite significant trend (B. subtilis, Streptomyces, pSymA and pSymB in S. meliloti). dN, dS, and ω were examined across all genes and there was no significant correlation between those values and distance from the origin. This study highlights the impact that genomic rearrangements and location have on molecular trends in some bacteria, illustrating the importance of considering spatial trends in molecular evolutionary analysis. Assuming that molecular trends are exclusively in one direction can be problematic.

The environment drives microbial trait variability in aquatic habitats

A prerequisite to improve the predictability of microbial community dynamics is to understand the mechanisms of microbial assembly. To study factors that contribute to microbial community assembly, we examined the temporal dynamics of genes in five aquatic metagenome time-series, originating from marine offshore or coastal sites and one lake. With this trait-based approach we expected to find gene-specific patterns of temporal allele variability that depended on the seasonal metacommunity size of carrier-taxa and the variability of the milieu and the substrates to which the resulting proteins were exposed. In more detail, we hypothesized that a larger seasonal metacommunity size would result in increased temporal variability of functional units (i.e., gene alleles), as shown previously for taxonomic units. We further hypothesized that multicopy genes would feature higher temporal variability than single-copy genes, as gene multiplication can result from high variability in substrate quality and quantity. Finally, we hypothesized that direct exposure of proteins to the extracellular environment would result in increased temporal variability of the respective gene compared to intracellular proteins that are less exposed to environmental fluctuations. The first two hypotheses were confirmed in all data sets, while significant effects of the subcellular location of gene products was only seen in three of the five time-series. The gene with the highest allele variability throughout all data sets was an iron transporter, also representing a target for phage infection. Previous work has emphasized the role of phage-prokaryote interactions as a major driver of microbial diversity. Our finding therefore points to a potentially important role of iron transporter-mediated phage infections for the assembly and maintenance of diversity in aquatic prokaryotes.

Do Mixed-Species Biofilms Dominate in Chronic Infections?-Need for in situ Visualization of Bacterial Organization

Chronic infections present a serious economic burden to health-care systems. The severity and prevalence of chronic infections are continuously increasing due to an aging population and an elevated number of lifestyle related diseases such as diabetes. Treatment of chronic infections has proven difficult, mainly due to the presence of biofilms that render bacteria more tolerant toward antimicrobials and the host immune response. Chronic infections have been described to harbor several different bacterial species and it has been hypothesized that microscale interactions and mixed-species consortia are present as described for most natural occurring biofilms i.e., aquatic systems and industrial settings, but also for some commensal human biofilms i.e., the mouth microbiota. However, the presence of mixed-species biofilms in chronic infections is most often an assumption based on culture-based methods and/or by means of molecular approaches, such as PCR and sequencing performed from homogenized bulk tissue samples. These methods disregard the spatial organization of the bacterial community and thus valuable information on biofilm aggregate composition, spatial organization, and possible interactions between different species is lost. Hitherto, only few studies have made visual in situ presentations of mixed-species biofilms in chronic infections, which is pivotal for the description of bacterial composition, spatial distribution, and interspecies interaction on the microscale. In order for bacteria to interact (synergism, commensalism, mutualism, competition, etc.) they need to be in close proximity to each other on the scale where they can affect e.g., solute concentrations. We argue that visual proof of mixed species biofilms in chronic infections is scarce compared to what is seen in e.g., environmental biofilms and call for a debate on the importance of mixed-species biofilm in chronic infections.

SilkDB 3.0: visualizing and exploring multiple levels of data for silkworm

SilkDB is an open-accessibility database and powerful platform that provides comprehensive information on the silkworm (Bombyx mori) genome. Since SilkDB 2.0 was released 10 years ago, vast quantities of data about multiple aspects of the silkworm have been generated, including genome, transcriptome, Hi-C and pangenome. To visualize data at these different biological levels, we present SilkDB 3.0 (https://silkdb.bioinfotoolkits.net), a visual analytic tool for exploring silkworm data through an interactive user interface. The database contains a high-quality chromosome-level assembly of the silkworm genome, and its coding sequences and gene sets are more accurate than those in the previous version. SilkDB 3.0 provides a view of the information for each gene at the levels of sequence, protein structure, gene family, orthology, synteny, genome organization and gives access to gene expression information, genetic variation and genome interaction map. A set of visualization tools are available to display the abundant information in the above datasets. With an improved interactive user interface for the integration of large data sets, the updated SilkDB 3.0 database will be a valuable resource for the silkworm and insect research community.

Leptospira spp., a genus in the stage of diversity and genomic data expansion

Leptospirosis is a widespread global zoonotic bacterial disease with a noteworthy human-animal-ecosystem interface. The disease presents different clinical manifestations and a high mortality and morbidity rates in humans and animals throughout the world. Characterization and correct classification of Leptospira isolates is essential for a better understanding the epidemiological properties of the disease. In the last ten years, molecular typing tools have been developed and applied to this field. These methods together with the availability of hundreds of new whole genome sequences that belong to known and new described species are shaping the understanding and structure of the entire genus.

Metatranscriptomics: an approach for retrieving novel eukaryotic genes from polluted and related environments

Metatranscriptomics, a subset of metagenomics, provides valuable information about the whole gene expression profiling of complex microbial communities of an ecosystem. Metagenomic studies mainly focus on the genomic content and identification of microbes present within a community, while metatranscriptomics provides the diversity of the active genes within such community, their expression profile and how these levels change due to change in environmental conditions. Metatranscriptomics has been applied to different types of environments, from the study of human microbiomes, to those found in plants, animals, within soils and in aquatic systems. Metatranscriptomics, based on the utilization of mRNA isolated from environmental samples, is a suitable approach to mine the eukaryotic gene pool for genes of biotechnological relevance. Also, it is imperative to develop different bioinformatic pipelines to analyse the data obtained from metatranscriptomic analysis. In the present review, we summarise the metatranscriptomics applied to soil environments to study the functional diversity, and discuss approaches for isolating the genes involved in organic matter degradation and providing tolerance to toxic metals, role of metatranscriptomics in microbiome research, various bioinformatics pipelines used in data analysis and technical challenges for gaining biologically meaningful insight of this approach.

proGenomes2: an improved database for accurate and consistent habitat, taxonomic and functional annotations of prokaryotic genomes

Microbiology depends on the availability of annotated microbial genomes for many applications. Comparative genomics approaches have been a major advance, but consistent and accurate annotations of genomes can be hard to obtain. In addition, newer concepts such as the pan-genome concept are still being implemented to help answer biological questions. Hence, we present proGenomes2, which provides 87 920 high-quality genomes in a user-friendly and interactive manner. Genome sequences and annotations can be retrieved individually or by taxonomic clade. Every genome in the database has been assigned to a species cluster and most genomes could be accurately assigned to one or multiple habitats. In addition, general functional annotations and specific annotations of antibiotic resistance genes and single nucleotide variants are provided. In short, proGenomes2 provides threefold more genomes, enhanced habitat annotations, updated taxonomic and functional annotation and improved linkage to the NCBI BioSample database. The database is available at http://progenomes.embl.de/.

Multiplexed Non-barcoded Long-Read Sequencing and Assembling Genomes of Bacillus Strains in Error-Free Simulations

The generation of genomic data from microorganisms has revolutionized our abilities to understand their biology, but it is still challenging to obtain complete genome sequences of microbes in an automated high-throughput and cost-effective manner. While the advent of second-generation sequencing technologies provided significantly higher throughput, their shorter lengths and more pronounced sequence-context bias led to a shift towards resequencing applications. Recently, single molecule real-time (SMRT) DNA sequencing has been used to generate sequencing reads that are much longer than other sequencing platforms, facilitating de novo genome assembly and genome finishing. Here we introduced a novel multiplex strategy to make full use of the capacity and characteristics of SMRT sequencing in microbe genome assembly. We used error-free simulations to evaluate the practicability of assembling SMRT genomic sequencing data from multiple microbes into finished genomes once at a time. Then we compared the influence of two key factors, including sequencing coverage and read length, on multiplex assembling. Our results showed that long-read genomic sequencing inherently provided the ability to assemble genomic sequencing data from multiple microbes into finished genomes due to its long length. This approach might be helpful for the various groups of microbial genome projects or metagenomics research.

In Silico Analysis of Gardnerella Genomospecies Detected in the Setting of Bacterial Vaginosis

BACKGROUND

Gardnerella vaginalis is implicated as one of the causative agents of bacterial vaginosis, but it can also be isolated from the vagina of healthy women. Previous efforts to study G. vaginalis identified 4 to 6 clades, but average nucleotide identity analysis indicates that G. vaginalis may be multiple species. Recently, Gardnerella was determined to be 13 genomospecies, with Gardnerella piottii, Gardnerella leopoldii, and Gardnerella swidsinkii delineated as separate species.

METHODS

We accessed 103 publicly available genomes annotated as G. vaginalis. We performed comprehensive taxonomic and phylogenomic analysis to quantify the number of species called G. vaginalis, the similarity of their core genes, and their burden of their accessory genes. We additionally analyzed publicly available metatranscriptomic data sets of bacterial vaginosis to determine whether the newly delineated genomospecies are present, and to identify putative conserved features of Gardnerella pathogenesis.

RESULTS

Gardnerella could be classified into 8 to 14 genomospecies depending on the in silico classification tools used. Consensus classification identified 9 different Gardnerella genomospecies, here annotated as GS01 through GS09. The genomospecies could be readily distinguished by the phylogeny of their shared genes and burden of accessory genes. All of the new genomospecies were identified in metatranscriptomes of bacterial vaginosis.

CONCLUSIONS

Multiple Gardnerella genomospecies operating in isolation or in concert with one another may be responsible for bacterial vaginosis. These results have important implications for future efforts to understand the evolution of the Gardnerella genomospecies, host-pathogen interactions of the genomospecies during bacterial vaginosis, diagnostic assay development for bacterial vaginosis, and metagenomic investigations of the vaginal microbiota.

A comprehensive genomic and growth proteomic analysis of antitumor lipopeptide bacillomycin Lb biosynthesis in Bacillus amyloliquefaciens X030

Lipopeptides (such as iturin, fengycin, and surfactin) from Bacillus possess antibacterial, antifungal, and antiviral activities and have important application in agriculture and pharmaceuticals. Although unremitting efforts have been devoted to improve lipopeptide production by designing gene regulatory circuits or optimizing fermentation process, little attention has been paid to utilizing multi-omics for systematically mining core genes and proteins during the bacterial growth cycle. Here, lipopeptide bacillomycin Lb from new Bacillus amyloliquefaciens X030 was isolated and first found to have anticancer activity in various cancer cells (such as SMMC-7721 and MDA-MB-231). A comprehensive genomic and growth proteomic analysis of X030 revealed bacillomycin Lb biosynthetic gene cluster, key enzymes and potential regulatory proteins (PerR, PhoP, CcpA, and CsfB), and novel links between primary metabolism and bacillomycin Lb production in X030. The antitumor activity of the fermentation supernatant supplemented with amino acids (such as glutamic acid) and sucrose was significantly increased, verifying the role of key metabolic switches in the metabolic regulatory network. Quantitative real-time PCR analysis confirmed that 7 differential expressed genes exhibited a positive correlation between changes at transcriptional and translational levels. The study not only will stimulate the deeper and wider antitumor study of lipopeptides but also provide a comprehensive database, which promotes an in-depth analysis of pathways and networks for complex events in lipopeptide biosynthesis and regulation and gives great help in improving the yield of bacillomycin Lb (media optimization, genetic modification, or pathway engineering).

An efficient Agrobacterium-mediated soybean transformation method using green fluorescent protein as a selectable marker

Genetic transformation plays a vital role in gene functional study and molecular breeding of soybean. Conventional soybean transformation methods using chemical selectable markers, such as antibiotic or herbicide resistance genes, rely on the identification of positive transgenic lines at advanced developmental stages, making selection procedure labor intensive and time consuming. Utilization of a visual maker to track the transgene would avoid the uncertainty and blindness in the transformation process. In this research, we used green fluorescent protein (GFP) as the selectable marker to detect transgenics at early stages of soybean development. Positive transformants were detected recurrently during each stage of the process based on visualization of the green fluorescence signal, which help us to discard the non-transgenic ones in each stage to reduce the unnecessary experimental cost and lab space. In addition, the positive transgenic seeds can be identified before planting for early detection of transgene and obtain homozygous lines in advance. The method established in this study is also a useful reference for other plant species.

Machine learning technology in the application of genome analysis: A systematic review

Machine learning (ML) is a powerful technique to tackle many problems in data mining and predictive analytics. We believe that ML will be of considerable potentials in the field of bioinformatics since the high-throughput technology is producing ever increasing biological data. In this review, we summarized major ML algorithms and conditions that must be paid attention to when applying these algorithms to genomic problems in details and we provided a list of examples from different perspectives and data analysis challenges at present.

Differential ratio amplicons (Ramp ) for the evaluation of RNA integrity extracted from complex environmental samples

Reliability and reproducibility of transcriptomics‐based studies are dependent on RNA integrity. In microbial ecology, microfluidics‐based techniques, such as the Ribosomal Integrity Number (RIN), targeting rRNA are currently the only approaches to evaluate RNA integrity. However, the relationship between rRNA and mRNA integrity is unknown. Here, we present an integrity index, the Ratio Amplicon, R_amp, adapted from human clinical studies, to directly monitor mRNA integrity from complex environmental samples. We show, in a suite of experimental degradations of RNA extracted from sediment, that while the RIN generally reflected the degradation status of RNA the R_amp mapped mRNA degradation better. Furthermore, we examined the effect of degradation on transcript community structure by amplicon sequencing of 16S rRNA, amoA and glnA transcripts. We successfully sequenced transcripts for all three targets even from highly‐degraded RNA samples. While RNA degradation changed the community structure of the mRNA profiles, no changes were observed for the 16S rRNA transcript profiles. Since both RT‐Q‐PCR and sequencing results were obtained, even from highly degraded samples, we strongly recommend evaluating RNA integrity prior to downstream processing to ensure meaningful results. For this, both the RIN and R_amp are useful, with the R_amp better evaluating mRNA integrity in this study.

Orphan Genes Shared by Pathogenic Genomes Are More Associated with Bacterial Pathogenicity

Recent pangenome analyses of numerous bacterial species have suggested that each genome of a single species may have a significant fraction of its gene content unique or shared by a very few genomes (i.e., ORFans). We selected nine bacterial genera, each containing at least five pathogenic and five nonpathogenic genomes, to compare their ORFans in relation to pathogenicity-related genes. Pathogens in these genera are known to cause a number of common and devastating human diseases such as pneumonia, diphtheria, melioidosis, and tuberculosis. Thus, they are worthy of in-depth systems microbiology investigations, including the comparative study of ORFans between pathogens and nonpathogens. We provide direct evidence to suggest that ORFans shared by more pathogens are more associated with pathogenicity-related genes and thus are more important targets for development of new diagnostic markers or therapeutic drugs for bacterial infectious diseases.

Orphan genes (also known as ORFans [i.e., orphan open reading frames]) are new genes that enable an organism to adapt to its specific living environment. Our focus in this study is to compare ORFans between pathogens (P) and nonpathogens (NP) of the same genus. Using the pangenome idea, we have identified 130,169 ORFans in nine bacterial genera (505 genomes) and classified these ORFans into four groups: (i) SS-ORFans (P), which are only found in a single pathogenic genome; (ii) SS-ORFans (NP), which are only found in a single nonpathogenic genome; (iii) PS-ORFans (P), which are found in multiple pathogenic genomes; and (iv) NS-ORFans (NP), which are found in multiple nonpathogenic genomes. Within the same genus, pathogens do not always have more genes, more ORFans, or more pathogenicity-related genes (PRGs)—including prophages, pathogenicity islands (PAIs), virulence factors (VFs), and horizontal gene transfers (HGTs)—than nonpathogens. Interestingly, in pathogens of the nine genera, the percentages of PS-ORFans are consistently higher than those of SS-ORFans, which is not true in nonpathogens. Similarly, in pathogens of the nine genera, the percentages of PS-ORFans matching the four types of PRGs are also always higher than those of SS-ORFans, but this is not true in nonpathogens. All of these findings suggest the greater importance of PS-ORFans for bacterial pathogenicity.

IMPORTANCE Recent pangenome analyses of numerous bacterial species have suggested that each genome of a single species may have a significant fraction of its gene content unique or shared by a very few genomes (i.e., ORFans). We selected nine bacterial genera, each containing at least five pathogenic and five nonpathogenic genomes, to compare their ORFans in relation to pathogenicity-related genes. Pathogens in these genera are known to cause a number of common and devastating human diseases such as pneumonia, diphtheria, melioidosis, and tuberculosis. Thus, they are worthy of in-depth systems microbiology investigations, including the comparative study of ORFans between pathogens and nonpathogens. We provide direct evidence to suggest that ORFans shared by more pathogens are more associated with pathogenicity-related genes and thus are more important targets for development of new diagnostic markers or therapeutic drugs for bacterial infectious diseases.

Sunflower pan-genome analysis shows that hybridization altered gene content and disease resistance

Domesticated plants and animals often display dramatic responses to selection, but the origins of the genetic diversity underlying these responses remain poorly understood. Despite domestication and improvement bottlenecks, the cultivated sunflower remains highly variable genetically, possibly due to hybridization with wild relatives. To characterize genetic diversity in the sunflower and to quantify contributions from wild relatives, we sequenced 287 cultivated lines, 17 Native American landraces and 189 wild accessions representing 11 compatible wild species. Cultivar sequences failing to map to the sunflower reference were assembled de novo for each genotype to determine the gene repertoire, or 'pan-genome', of the cultivated sunflower. Assembled genes were then compared to the wild species to estimate origins. Results indicate that the cultivated sunflower pan-genome comprises 61,205 genes, of which 27% vary across genotypes. Approximately 10% of the cultivated sunflower pan-genome is derived through introgression from wild sunflower species, and 1.5% of genes originated solely through introgression. Gene ontology functional analyses further indicate that genes associated with biotic resistance are over-represented among introgressed regions, an observation consistent with breeding records. Analyses of allelic variation associated with downy mildew resistance provide an example in which such introgressions have contributed to resistance to a globally challenging disease.

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.

Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications

The PubMLST.org website hosts a collection of open-access, curated databases that integrate population sequence data with provenance and phenotype information for over 100 different microbial species and genera.  Although the PubMLST website was conceived as part of the development of the first multi-locus sequence typing (MLST) scheme in 1998 the software it uses, the Bacterial Isolate Genome Sequence database (BIGSdb, published in 2010), enables PubMLST to include all levels of sequence data, from single gene sequences up to and including complete, finished genomes.  Here we describe developments in the BIGSdb software made from publication to June 2018 and show how the platform realises microbial population genomics for a wide range of applications.  The system is based on the gene-by-gene analysis of microbial genomes, with each deposited sequence annotated and curated to identify the genes present and systematically catalogue their variation.  Originally intended as a means of characterising isolates with typing schemes, the synthesis of sequences and records of genetic variation with provenance and phenotype data permits highly scalable (whole genome sequence data for tens of thousands of isolates) means of addressing a wide range of functional questions, including: the prediction of antimicrobial resistance; likely cross-reactivity with vaccine antigens; and the functional activities of different variants that lead to key phenotypes.  There are no limitations to the number of sequences, genetic loci, allelic variants or schemes (combinations of loci) that can be included, enabling each database to represent an expanding catalogue of the genetic variation of the population in question.  In addition to providing web-accessible analyses and links to third-party analysis and visualisation tools, the BIGSdb software includes a RESTful application programming interface (API) that enables access to all the underlying data for third-party applications and data analysis pipelines.

An efficient classification algorithm for NGS data based on text similarity

With the advancement of high-throughput sequencing technologies, the amount of available sequencing data is growing at a pace that has now begun to greatly challenge the data processing and storage capacities of modern computer systems. Removing redundancy from such data by clustering could be crucial for reducing memory, disk space and running time consumption. In addition, it also has good performance on reducing dataset noise in some analysis applications. In this study, we propose a high-performance short sequence classification algorithm (HSC) for next generation sequencing (NGS) data based on efficient hash function and text similarity. First, HSC converts all reads into k-mers, then it forms a unique k-mer set by merging the duplicated and reverse complementary elements. Second, all unique k-mers are stored in a hash table, where the k-mer string is stored in the key field, and the ID of the reads containing the k-mer are stored in the value field. Third, each hash unit is transformed into a short text consisting of reads. Fourth, texts that satisfy the similarity threshold are combined into a long text, the merge operation is executed iteratively until there is no text that satisfies the merge condition. Finally, the long text is transformed into a cluster consisting of reads. We tested HSC using five real datasets. The experimental results showed that HSC cluster 100 million short reads within 2 hours, and it has excellent performance in reducing memory consumption. Compared to existing methods, HSC is much faster than other tools, it can easily handle tens of millions of sequences. In addition, when HSC is used as a preprocessing tool to produce assembly data, the memory and time consumption of the assembler is greatly reduced. It can help the assembler to achieve better assemblies in terms of N50, NA50 and genome fraction.

Phenotypic Variation during Biofilm Formation: Implications for Anti-Biofilm Therapeutic Design

Various bacterial species cycle between growth phases and biofilm formation, of which the latter facilitates persistence in inhospitable environments. These phases can be generally characterized by one or more cellular phenotype(s), each with distinct virulence factor functionality. In addition, a variety of phenotypes can often be observed within the phases themselves, which can be dependent on host conditions or the presence of nutrient and oxygen gradients within the biofilm itself (i.e., microenvironments). Currently, most anti-biofilm strategies have targeted a single phenotype; this approach has driven effective, yet incomplete, protection due to the lack of consideration of gene expression dynamics throughout the bacteria’s pathogenesis. As such, this article provides an overview of the distinct phenotypes found within each biofilm development phase and demonstrates the unique anti-biofilm solutions each phase offers. However, we conclude that a combinatorial approach must be taken to provide complete protection against biofilm forming bacterial and their resulting diseases.

Current Challenges of Streptococcus Infection and Effective Molecular, Cellular, and Environmental Control Methods in Aquaculture

Several bacterial etiological agents of streptococcal disease have been associated with fish mortality and serious global economic loss. Bacterial identification based on biochemical, molecular, and phenotypic methods has been routinely used, along with assessment of morphological analyses. Among these, the molecular method of 16S rRNA sequencing is reliable, but presently, advanced genomics are preferred over other traditional identification methodologies. This review highlights the geographical variation in strains, their relatedness, as well as the complexity of diagnosis, pathogenesis, and various control methods of streptococcal infections. Several limitations, from diagnosis to control, have been reported, which make prevention and containment of streptococcal disease difficult. In this review, we discuss the challenges in diagnosis, pathogenesis, and control methods and suggest appropriate molecular (comparative genomics), cellular, and environmental solutions from among the best available possibilities.

CADS: CRISPR/Cas12a-Assisted DNA Steganography for Securing the Storage and Transfer of DNA-Encoded Information

Because DNA has the merit of high capacity and complexity, DNA steganography, which conceals DNA-encoded messages, is very promising in information storage. The classical DNA steganography method hides DNA with a "secret message" in a mount of junk DNA, and the message can be extracted by polymerase chain reaction (PCR) using specific primers (key), followed by DNA sequencing and sequence decoding. As leakage of the primer information may result in message insecurity, new methods are needed to better secure the DNA information. Here, we develop a pre-key by either mixing specific primers (real key) with nonspecific primers (fake key) or linking a real key with 3'-end redundant sequences. Then, the single-stranded DNA (ssDNA) trans cleavage activity of CRISPR/Cas12a is employed to cut a fake key or remove the 3'-end redundant sequences, generating a real key for further information extraction. Therefore, with the Cas12a-assisted DNA steganography method, both storage and transfer of DNA-encoding data can be better protected.

Microbiome of Total Versus Live Bacteria in the Gut of Rex Rabbits

Gastrointestinal bacteria are essential for host health, and only viable microorganisms contribute to gastrointestinal functions. When evaluating the gut microbiota by next generation sequencing method, dead bacteria, which compose a proportion of gut bacteria, may distort analysis of the live gut microbiota. We collected stomach, jejunum, ileum, cecum, and colon contents from Rex rabbits. A modified propidium monoazide (PMA) treatment protocol was used to exclude DNA from dead bacteria. Analysis of untreated samples yielded total bacteria, and analysis of PMA-treated samples yielded live bacteria. Quantitative polymerase chain reaction and 16S rRNA gene sequencing were performed to evaluate the live-to-total bacteria ratio and compare the difference between live and total microbiota in the entire digestive tract. A low proportion of live bacteria in the foregut (stomach 1.12%, jejunum 1.2%, ileum 2.84%) and a high proportion of live bacteria in the hindgut (cecum 24.66%, colon 19.08%) were observed. A significant difference existed between total and live microbiota. Clostridiales, Ruminococcaceae, and S24-7 dominated the hindgut of both groups, while Acinetobacter and Cupriavidus dominated only in live foregut microbiota. Clostridiales and Ruminococcaceae abundance decreased, while S24-7 increased in live hindgut microbiota. The alpha- and beta-diversities differed significantly between groups. Analysis of networks showed the mutual relationship between live bacteria differed vastly when compared with total bacteria. Our study revealed a large number of dead bacteria existed in the digestive tract of Rex rabbits and distorted the community profile of the live microbiota. Total bacteria is an improper representation of the live gut microbiota, particularly in the foregut.

A Retrospective Review of Microbiological Methods Applied in Studies Following the Deepwater Horizon Oil Spill

The Deepwater Horizon (DWH) oil spill in the Gulf of Mexico in 2010 resulted in serious damage to local marine and coastal environments. In addition to the physical removal and chemical dispersion of spilled oil, biodegradation by indigenous microorganisms was regarded as the most effective way for cleaning up residual oil. Different microbiological methods were applied to investigate the changes and responses of bacterial communities after the DWH oil spills. By summarizing and analyzing these microbiological methods, giving recommendations and proposing some methods that have not been used, this review aims to provide constructive guidelines for microbiological studies after environmental disasters, especially those involving organic pollutants.

Core Genome Multilocus Sequence Typing: a Standardized Approach for Molecular Typing of Mycoplasma gallisepticum

Mycoplasma gallisepticum is the most virulent and economically important Mycoplasma species for poultry worldwide. Currently, M. gallisepticum strain differentiation based on sequence analysis of 5 loci remains insufficient for accurate outbreak investigation. Recently, whole-genome sequences (WGS) of many human and animal pathogens have been successfully used for microbial outbreak investigations. However, the massive sequence data and the diverse properties of different genes within bacterial genomes results in a lack of standard reproducible methods for comparisons among M. gallisepticum whole genomes. Here, we proposed the development of a core genome multilocus sequence typing (cgMLST) scheme for M. gallisepticum strains and field isolates. For development of this scheme, a diverse collection of 37 M. gallisepticum genomes was used to identify cgMLST targets. A total of 425 M. gallisepticum conserved genes (49.85% of M. gallisepticum genome) were selected as core genome targets. A total of 81 M. gallisepticum genomes from 5 countries on 4 continents were typed using M. gallisepticum cgMLST. Analyses of phylogenetic trees generated by cgMLST displayed a high degree of agreement with geographical and temporal information. Moreover, the high discriminatory power of cgMLST allowed differentiation between M. gallisepticum strains of the same outbreak. M. gallisepticum cgMLST represents a standardized, accurate, highly discriminatory, and reproducible method for differentiation among M. gallisepticum isolates. cgMLST provides stable and expandable nomenclature, allowing for comparison and sharing of typing results among laboratories worldwide. cgMLST offers an opportunity to harness the tremendous power of next-generation sequencing technology in applied avian mycoplasma epidemiology at both local and global levels.

Vibrio tapetis Displays an Original Type IV Secretion System in Strains Pathogenic for Bivalve Molluscs

The Brown Ring Disease (BRD) caused high mortality rates since 1986 in the Manila clam Venerupis philippinarum introduced and cultured in Western Europe from the 1970s. The causative agent of BRD is a Gram-Negative bacterium, Vibrio tapetis, which is also pathogenic to fish. Here we report the first assembly of the complete genome of V. tapetis CECT4600^T, together with the genome sequences of 16 additional strains isolated across a broad host and geographic range. Our extensive genome dataset allowed us to describe the pathogen pan- and core genomes and to identify putative virulence factors. The V. tapetis core genome consists of 3,352 genes, including multiple potential virulence factors represented by haemolysins, transcriptional regulators, Type I restriction modification system, GGDEF domain proteins, several conjugative plasmids, and a Type IV secretion system. Future research on the coevolutionary arms race between V. tapetis virulence factors and host resistance mechanisms will improve our understanding of how pathogenicity develops in this emerging pathogen.

Strain profiling and epidemiology of bacterial species from metagenomic sequencing

Microbial communities are often composed by complex mixtures of multiple strains of the same species, characterized by a wide genomic and phenotypic variability. Computational methods able to identify, quantify and classify the different strains present in a sample are essential to fully exploit the potential of metagenomic sequencing in microbial ecology, with applications that range from the epidemiology of infectious diseases to the characterization of the dynamics of microbial colonization. Here we present a computational approach that uses the available genomic data to reconstruct complex strain profiles from metagenomic sequencing, quantifying the abundances of the different strains and cataloging them according to the population structure of the species. We validate the method on synthetic data sets and apply it to the characterization of the strain distribution of several important bacterial species in real samples, showing how its application provides novel insights on the structure and complexity of the microbiota.

Evolution of Salmonella-Host Cell Interactions through a Dynamic Bacterial Genome

Salmonella Typhimurium has a broad arsenal of genes that are tightly regulated and coordinated to facilitate adaptation to the various host environments it colonizes. The genome of Salmonella Typhimurium has undergone multiple gene acquisition events and has accrued changes in non-coding DNA that have undergone selection by regulatory evolution. Together, at least 17 horizontally acquired pathogenicity islands (SPIs), prophage-associated genes, and changes in core genome regulation contribute to the virulence program of Salmonella. Here, we review the latest understanding of these elements and their contributions to pathogenesis, emphasizing the regulatory circuitry that controls niche-specific gene expression. In addition to an overview of the importance of SPI-1 and SPI-2 to host invasion and colonization, we describe the recently characterized contributions of other SPIs, including the antibacterial activity of SPI-6 and adhesion and invasion mediated by SPI-4. We further discuss how these fitness traits have been integrated into the regulatory circuitry of the bacterial cell through cis-regulatory evolution and by a careful balance of silencing and counter-silencing by regulatory proteins. Detailed understanding of regulatory evolution within Salmonella is uncovering novel aspects of infection biology that relate to host-pathogen interactions and evasion of host immunity.

Theoretical microbial ecology without species

Ecosystems are commonly conceptualized as networks of interacting species. However, partitioning natural diversity of organisms into discrete units is notoriously problematic and mounting experimental evidence raises the intriguing question whether this perspective is appropriate for the microbial world. Here an alternative formalism is proposed that does not require postulating the existence of species as fundamental ecological variables and provides a naturally hierarchical description of community dynamics. This formalism allows approaching the species problem from the opposite direction. While the classical models treat a world of imperfectly clustered organism types as a perturbation around well-clustered species, the presented approach allows gradually adding structure to a fully disordered background. The relevance of this theoretical construct for describing highly diverse natural ecosystems is discussed.

A Robust Framework for Microbial Archaeology

Microbial archaeology is flourishing in the era of high-throughput sequencing, revealing the agents behind devastating historical plagues, identifying the cryptic movements of pathogens in prehistory, and reconstructing the ancestral microbiota of humans. Here, we introduce the fundamental concepts and theoretical framework of the discipline, then discuss applied methodologies for pathogen identification and microbiome characterization from archaeological samples. We give special attention to the process of identifying, validating, and authenticating ancient microbes using high-throughput DNA sequencing data. Finally, we outline standards and precautions to guide future research in the field.