An overlooked phenomenon: complex interactions of potential error sources on the quality of bacterial de novo genome assemblies.

BACKGROUND: Parameters adversely affecting the contiguity and accuracy of the assemblies from Illumina next-generation sequencing (NGS) are well described. However, past studies generally focused on their additive effects, overlooking their potential interactions possibly exacerbating one another's effects in a multiplicative manner. To investigate whether or not they act interactively on de novo genome assembly quality, we simulated sequencing data for 13 bacterial reference genomes, with varying levels of error rate, sequencing depth, PCR and optical duplicate ratios. RESULTS: We assessed the quality of assemblies from the simulated sequencing data with a number of contiguity and accuracy metrics, which we used to quantify both additive and multiplicative effects of the four parameters. We found that the tested parameters are engaged in complex interactions, exerting multiplicative, rather than additive, effects on assembly quality. Also, the ratio of non-repeated regions and GC% of the original genomes can shape how the four parameters affect assembly quality. CONCLUSIONS: We provide a framework for consideration in future studies using de novo genome assembly of bacterial genomes, e.g. in choosing the optimal sequencing depth, balancing between its positive effect on contiguity and negative effect on accuracy due to its interaction with error rate. Furthermore, the properties of the genomes to be sequenced also should be taken into account, as they might influence the effects of error sources themselves.

Disease-Associated Streptococcus pneumoniae Genetic Variation.

Streptococcus pneumoniae is an opportunistic pathogen that causes substantial illness and death among children worldwide. The genetic backgrounds of pneumococci that cause infection versus asymptomatic carriage vary substantially. To determine the evolutionary mechanisms of opportunistic pathogenicity, we conducted a genomic surveillance study in China. We collected 783 S. pneumoniae isolates from infected and asymptomatic children. By using a 2-stage genomewide association study process, we compared genomic differences between infection and carriage isolates to address genomic variation associated with pathogenicity. We identified 8 consensus k-mers associated with adherence, antimicrobial resistance, and immune modulation, which were unevenly distributed in the infection isolates. Classification accuracy of the best k-mer predictor for S. pneumoniae infection was good, giving a simple target for predicting pathogenic isolates. Our findings suggest that S. pneumoniae pathogenicity is complex and multifactorial, and we provide genetic evidence for precise targeted interventions.

In Silico Evaluation of Variant Calling Methods for Bacterial Whole-Genome Sequencing Assays.

Identification and analysis of clinically relevant strains of bacteria increasingly relies on whole-genome sequencing. The downstream bioinformatics steps necessary for calling variants from short-read sequences are well-established but seldom validated against haploid genomes. We devised an in silico workflow to introduce single nucleotide polymorphisms (SNP) and indels into bacterial reference genomes, and computationally generate sequencing reads based on the mutated genomes. We then applied the method to Mycobacterium tuberculosis H37Rv, Staphylococcus aureus NCTC 8325, and Klebsiella pneumoniae HS11286, and used the synthetic reads as truth sets for evaluating several popular variant callers. Insertions proved especially challenging for most variant callers to correctly identify, relative to deletions and single nucleotide polymorphisms. With adequate read depth, however, variant callers that use high quality soft-clipped reads and base mismatches to perform local realignment consistently had the highest precision and recall in identifying insertions and deletions ranging from1 to 50 bp. The remaining variant callers had lower recall values associated with identification of insertions greater than 20 bp.

Application and Challenge of 3rd Generation Sequencing for Clinical Bacterial Studies.

Over the past 25 years, the powerful combination of genome sequencing and bioinformatics analysis has played a crucial role in interpreting information encoded in bacterial genomes. High-throughput sequencing technologies have paved the way towards understanding an increasingly wide range of biological questions. This revolution has enabled advances in areas ranging from genome composition to how proteins interact with nucleic acids. This has created unprecedented opportunities through the integration of genomic data into clinics for the diagnosis of genetic traits associated with disease. Since then, these technologies have continued to evolve, and recently, long-read sequencing has overcome previous limitations in terms of accuracy, thus expanding its applications in genomics, transcriptomics and metagenomics. In this review, we describe a brief history of the bacterial genome sequencing revolution and its application in public health and molecular epidemiology. We present a chronology that encompasses the various technological developments: whole-genome shotgun sequencing, high-throughput sequencing, long-read sequencing. We mainly discuss the application of next-generation sequencing to decipher bacterial genomes. Secondly, we highlight how long-read sequencing technologies go beyond the limitations of traditional short-read sequencing. We intend to provide a description of the guiding principles of the 3rd generation sequencing applications and ongoing improvements in the field of microbial medical research.

Bacterial Protein Interaction Networks: Connectivity is Ruled by Gene Conservation, Essentiality and Function.

BACKGROUND: Protein-protein interaction (PPI) networks are the backbone of all processes in living cells. In this work, we relate conservation, essentiality and functional repertoire of a gene to the connectivity k (i.e. the number of interactions, links) of the corresponding protein in the PPI network. METHODS: On a set of 42 bacterial genomes of different sizes, and with reasonably separated evolutionary trajectories, we investigate three issues: i) whether the distribution of connectivities changes between PPI subnetworks of essential and nonessential genes; ii) how gene conservation, measured both by the evolutionary retention index (ERI) and by evolutionary pressures, is related to the connectivity of the corresponding protein; iii) how PPI connectivities are modulated by evolutionary and functional relationships, as represented by the Clusters of Orthologous Genes (COGs). RESULTS: We show that conservation, essentiality and functional specialisation of genes constrain the connectivity of the corresponding proteins in bacterial PPI networks. In particular, we isolated a core of highly connected proteins (connectivities k≥40), which is ubiquitous among the species considered here, though mostly visible in the degree distributions of bacteria with small genomes (less than 1000 genes). CONCLUSION: The genes that support this highly connected core are conserved, essential and, in most cases, belong to the COG cluster J, related to ribosomal functions and the processing of genetic information.

Gene duplication and deletion, not horizontal transfer, drove intra-species mosaicism of Bartonella henselae.

Bartonella henselae is a facultative intracellular pathogen that occurs worldwide and is responsible primarily for cat-scratch disease in young people and bacillary angiomatosis in immunocompromised patients. The principal source of genome-level diversity that contributes to B. henselae's host-adaptive features is thought to be horizontal gene transfer events. However, our analyses did not reveal the acquisition of horizontally-transferred islands in B. henselae after its divergence from other Bartonella. Rather, diversity in gene content and genome size was apparently acquired through two alternative mechanisms, including deletion and, more predominantly, duplication of genes. Interestingly, a majority of these events occurred in regions that were horizontally transferred long before B. henselae's divergence from other Bartonella species. Our study indicates the possibility that gene duplication, in response to positive selection pressures in specific clones of B. henselae, might be linked to the pathogen's adaptation to arthropod vectors, the cat reservoir, or humans as incidental host-species.

Unique k-mers as Strain-Specific Barcodes for Phylogenetic Analysis and Natural Microbiome Profiling.

The need for a comparative analysis of natural metagenomes stimulated the development of new methods for their taxonomic profiling. Alignment-free approaches based on the search for marker k-mers turned out to be capable of identifying not only species, but also strains of microorganisms with known genomes. Here, we evaluated the ability of genus-specific k-mers to distinguish eight phylogroups of Escherichia coli (A, B1, C, E, D, F, G, B2) and assessed the presence of their unique 22-mers in clinical samples from microbiomes of four healthy people and four patients with Crohn's disease. We found that a phylogenetic tree inferred from the pairwise distance matrix for unique 18-mers and 22-mers of 124 genomes was fully consistent with the topology of the tree, obtained with concatenated aligned sequences of orthologous genes. Therefore, we propose strain-specific "barcodes" for rapid phylotyping. Using unique 22-mers for taxonomic analysis, we detected microbes of all groups in human microbiomes; however, their presence in the five samples was significantly different. Pointing to the intraspecies heterogeneity of E. coli in the natural microflora, this also indicates the feasibility of further studies of the role of this heterogeneity in maintaining population homeostasis.

Whole genome sequencing of Salmonella Chester reveals geographically distinct clusters, Norway, 2000 to 2016.

IntroductionDuring summer 2016, Norway observed an increase in Salmonella enterica subsp. enterica serovar Chester cases among travellers to Greece.AimOur aim was to investigate genetic relatedness of S. Chester for surveillance and outbreak detection by core genome multilocus sequence typing (cgMLST) and compare the results to genome mapping.MethodsWe included S. Chester isolates from 51 cases of salmonellosis between 2000 and 2016. Paired-end sequencing (2 × 250 bp) was performed on Illumina MiSeq. Genetic relatedness by cgMLST for Salmonella enterica subsp. enterica, including 3,002 genes and seven housekeeping genes, was compared by reference genome mapping with CSI Phylogeny version 1.4 and conventional MLST.ResultsConfirmed travel history was available for 80% of included cases, to Europe (n = 13), Asia (n = 12) and Africa (n = 16). Isolates were distributed into four phylogenetic clusters corresponding to geographical regions. Sequence type (ST) ST411 and a single-locus variant ST5260 (n = 17) were primarily acquired in southern Europe, ST1954 (n = 15) in Africa, ST343 (n = 11) and ST2063 (n = 8) primarily in Asia. Part of the European cluster was further divided into a Greek (n = 10) and a Cypriot (n = 4) cluster. All isolates in the African cluster displayed resistance to ≥ 1 class of antimicrobials, while resistance was rare in the other clusters.ConclusionWhole genome sequencing of S. Chester in Norway showed four geographically distinct clusters, with a possible outbreak occurring during summer 2016 related to Greece. We recommend public health institutes to implement cgMLST-based real-time Salmonella enterica surveillance for early and accurate detection of future outbreaks and further development of cluster cut-offs.

Impact of Recombination on the Base Composition of Bacteria and Archaea.

The mutational process in bacteria is biased toward A and T, and most species are GC-rich relative to the mutational input to their genome. It has been proposed that the shift in base composition is an adaptive process-that natural selection operates to increase GC-contents-and there is experimental evidence that bacterial strains with GC-rich versions of genes have higher growth rates than those strains with AT-rich versions expressing identical proteins. Alternatively, a nonadaptive process, GC-biased gene conversion (gBGC), could also increase the GC-content of DNA due to the mechanistic bias of gene conversion events during recombination. To determine what role recombination plays in the base composition of bacterial genomes, we compared the spectrum of nucleotide polymorphisms introduced by recombination in all microbial species represented by large numbers of sequenced strains. We found that recombinant alleles are consistently biased toward A and T, and that the magnitude of AT-bias introduced by recombination is similar to that of mutations. These results indicate that recombination alone, without the intervention of selection, is unlikely to counteract the AT-enrichment of bacterial genomes.

Transmissible Mycobacterium tuberculosis Strains Share Genetic Markers and Immune Phenotypes.

RATIONALE: Successful transmission of tuberculosis depends on the interplay of human behavior, host immune responses, and Mycobacterium tuberculosis virulence factors. Previous studies have been focused on identifying host risk factors associated with increased transmission, but the contribution of specific genetic variations in mycobacterial strains themselves are still unknown. OBJECTIVES: To identify mycobacterial genetic markers associated with increased transmissibility and to examine whether these markers lead to altered in vitro immune responses. METHODS: Using a comprehensive tuberculosis registry (n = 10,389) and strain collection in the Netherlands, we identified a set of 100 M. tuberculosis strains either least or most likely to be transmitted after controlling for host factors. We subjected these strains to whole-genome sequencing and evolutionary convergence analysis, and we repeated this analysis in an independent validation cohort. We then performed immunological experiments to measure in vitro cytokine production and neutrophil responses to a subset of the original strains with or without the identified mutations associated with increased transmissibility. MEASUREMENTS AND MAIN RESULTS: We identified the loci espE, PE-PGRS56, Rv0197, Rv2813-2814c, and Rv2815-2816c as targets of convergent evolution among transmissible strains. We validated four of these regions in an independent set of strains, and we demonstrated that mutations in these targets affected in vitro monocyte and T-cell cytokine production, neutrophil reactive oxygen species release, and apoptosis. CONCLUSIONS: In this study, we identified genetic markers in convergent evolution of M. tuberculosis toward enhanced transmissibility in vivo that are associated with altered immune responses in vitro.

A practical exact maximum compatibility algorithm for reconstruction of recent evolutionary history.

BACKGROUND: Maximum compatibility is a method of phylogenetic reconstruction that is seldom applied to molecular sequences. It may be ideal for certain applications, such as reconstructing phylogenies of closely-related bacteria on the basis of whole-genome sequencing. RESULTS: Here I present an algorithm that rapidly computes phylogenies according to a compatibility criterion. Although based on solutions to the maximum clique problem, this algorithm deals properly with ambiguities in the data. The algorithm is applied to bacterial data sets containing up to nearly 2000 genomes with several thousand variable nucleotide sites. Run times are several seconds or less. Computational experiments show that maximum compatibility is less sensitive than maximum parsimony to the inclusion of nucleotide data that, though derived from actual sequence reads, has been identified as likely to be misleading. CONCLUSIONS: Maximum compatibility is a useful tool for certain phylogenetic problems, such as inferring the relationships among closely-related bacteria from whole-genome sequence data. The algorithm presented here rapidly solves fairly large problems of this type, and provides robustness against misleading characters than can pollute large-scale sequencing data.

BugMat and FindNeighbour: command line and server applications for investigating bacterial relatedness.

BACKGROUND: Large scale bacterial sequencing has made the determination of genetic relationships within large sequence collections of bacterial genomes derived from the same microbial species an increasingly common task. Solutions to the problem have application to public health (for example, in the detection of possible disease transmission), and as part of divide-and-conquer strategies selecting groups of similar isolates for computationally intensive methods of phylogenetic inference using (for example) maximal likelihood methods. However, the generation and maintenance of distance matrices is computationally intensive, and rapid methods of doing so are needed to allow translation of microbial genomics into public health actions. RESULTS: We developed, tested and deployed three solutions. BugMat is a fast C++ application which generates one-off in-memory distance matrices. FindNeighbour and FindNeighbour2 are server-side applications which build, maintain, and persist either complete (for FindNeighbour) or sparse (for FindNeighbour2) distance matrices given a set of sequences. FindNeighbour and BugMat use a variation model to accelerate computation, while FindNeighbour2 uses reference-based compression. Performance metrics show scalability into tens of thousands of sequences, with options for scaling further. CONCLUSION: Three applications, each with distinct strengths and weaknesses, are available for distance-matrix based analysis of large bacterial collections. Deployed as part of the Public Health England solution for M. tuberculosis genomic processing, they will have wide applicability.

Estimating the Frequency of Horizontal Gene Transfer Using Phylogenetic Models of Gene Gain and Loss.

We analyze patterns of gene presence and absence in a maximum likelihood framework with rate parameters for gene gain and loss. Standard methods allow independent gains and losses in different parts of a tree. While losses of the same gene are likely to be frequent, multiple gains need to be considered carefully. A gene gain could occur by horizontal transfer or by origin of a gene within the lineage being studied. If a gene is gained more than once, then at least one of these gains must be a horizontal transfer. A key parameter is the ratio of gain to loss rates, a/v We consider the limiting case known as the infinitely many genes model, where a/v tends to zero and a gene cannot be gained more than once. The infinitely many genes model is used as a null model in comparison to models that allow multiple gains. Using genome data from cyanobacteria and archaea, it is found that the likelihood is significantly improved by allowing for multiple gains, but the average a/v is very small. The fraction of genes whose presence/absence pattern is best explained by multiple gains is only 15% in the cyanobacteria and 20% and 39% in two data sets of archaea. The distribution of rates of gene loss is very broad, which explains why many genes follow a treelike pattern of vertical inheritance, despite the presence of a significant minority of genes that undergo horizontal transfer.

Bacterial spoilers of food: behavior, fitness and functional properties.

Most food products are highly perishable as they constitute a rich nutrient source for microbial development. Among the microorganisms contaminating food, some present metabolic activities leading to spoilage. In addition to hygienic rules to reduce contamination, various treatments are applied during production and storage to avoid the growth of unwanted microbes. The nature and appearance of spoilage therefore depend on the physiological state of spoilers and on their ability to resist the processing/storage conditions and flourish on the food matrix. Spoilage also relies on the interactions between the microorganisms composing the ecosystems encountered in food. The recent rapid increase in publicly available bacterial genome sequences, as well as the access to high-throughput methods, should lead to a better understanding of spoiler behavior and to the possibility of decreasing food spoilage. This review lists the main bacterial species identified as food spoilers, their ability to develop during storage and/or processing, and the functions potentially involved in spoilage. We have also compiled an inventory of the available genome sequences of species encompassing spoilage strains. Combining in silico analysis of genome sequences with experimental data is proposed in order to understand and thus control the bacterial spoilage of food better.

DICEP: An integrative approach to augmenting genomic island detection.

Mobilization of clusters of genes called genomic islands (GIs) across bacterial lineages facilitates dissemination of traits, such as, resistance against antibiotics, virulence or hypervirulence, and versatile metabolic capabilities. Robust delineation of GIs is critical to understanding bacterial evolution that has a vast impact on different life forms. Methods for identification of GIs exploit different evolutionary features or signals encoded within the genomes of bacteria, however, the current state-of-the-art in GI detection still leaves much to be desired. Here, we have taken a combinatorial approach that accounted for GI specific features such as compositional bias, aberrant phyletic pattern, and marker gene enrichment within an integrative framework to delineate GIs in bacterial genomes. Our GI prediction tool, DICEP, was assessed on simulated genomes and well-characterized bacterial genomes. DICEP compared favorably with current GI detection tools on real and synthetic datasets.

Arcobacteraceae comparative genome analysis demonstrates genome heterogeneity and reduction in species isolated from animals and associated with human illness.

The Arcobacteraceae family groups Gram-negative bacterial species previously included in the family Campylobacteraceae. These species of which some are considered foodborne pathogens, have been isolated from different environmental niches and hosts. They have been isolated from various types of foods, though predominantly from food of animal origin, as well as from stool of humans with enteritis. Their different abilities to survive in different hosts and environments suggest an evolutionary pressure with consequent variation in their genome content. Moreover, their different physiological and genomic characteristics led to the recent proposal to create new genera within this family, which is however criticized due to the lack of discriminatory features and biological and clinical relevance. Aims of the present study were to assess the Arcobacteraceae pangenome, and to characterize existing similarities and differences in 20 validly described species. For this, analysis has been conducted on the genomes of the corresponding type strains obtained by Illumina sequencing, applying several bioinformatic tools. Results of the present study do not support the proposed division into different genera and revealed the presence of pangenome partitions with numbers comparable to other Gram-negative bacteria genera, such as Campylobacter. Different gene class compositions in animal and human-associated species are present, including a higher percentage of virulence-related gene classes such as cell motility genes. The adaptation to environmental and/or host conditions of some species was identified by the presence of specific genes. Furthermore, a division into pathogenic and non-pathogenic species is suggested, which can support future research on food safety and public health.

INTERPIN: A repository for intrinsic transcription termination hairpins in bacteria.

The large-scale detection of putative intrinsic transcription terminators is limited to only a few bacteria currently. We discovered a group of hairpins, called cluster hairpins, present within 15 nucleotides from each other. These are expected to work in tandem to cause intrinsic transcription termination (ITT), while the single hairpin can do the same alone. Therefore, exploring these ITT sites and the hairpins across bacterial genomes becomes highly desirable. INTERPIN is the largest archived collection of in silico inferred ITT hairpins in bacteria, covering 12745 bacterial genomes and encompassing ten bacterial phyla for ∼25 million hairpins. Users can obtain details on operons, individual cluster, and single ITT hairpins that were screened therein. Integrated Genome Viewer (IGV) software interactively visualizes hairpin secondary and tertiary structures in the genomic context. We also discuss statistics for the occurrence of cluster or single hairpins and other termination alternatives while showing the validation of predicted hairpins against in vivo detected hairpins. The database is freely available at http://pallab.cds.iisc.ac.in/INTERPIN/. INTERPIN (database and software) can make predictions for both AT and GC-rich genomes, which has not been achieved by any other program so far. It can also be used to improve genome annotation as well as to get predictions to improve the understanding of the ITT pathway by further analysis.

Integrated Human Skin Bacteria Genome Catalog Reveals Extensive Unexplored Habitat-Specific Microbiome Diversity and Function.

The skin is the largest organ in the human body. Various skin environments on its surface constitutes a complex ecosystem. One of the characteristics of the skin micro-ecosystem is low biomass, which greatly limits a comprehensive identification of the microbial species through sequencing. In this study, deep-shotgun sequencing (average 21.5 Gigabyte (Gb)) from 450 facial samples and publicly available skin metagenomic datasets of 2069 samples to assemble a Unified Human Skin Genome (UHSG) catalog is integrated. The UHSG encompasses 813 prokaryotic species derived from 5779 metagenome-assembled genomes, among which 470 are novel species covering 20 phyla with 1385 novel assembled genomes. Based on the UHSG, the core functions of the skin microbiome are described and the differences in amino acid metabolism, carbohydrate metabolism, and drug resistance functions among different phyla are identified. Furthermore, analysis of secondary metabolites of the near-complete genomes further find 1220 putative novel secondary metabolites, several of which are found in previously unknown genomes. Single nucleotide variant (SNV) reveals a possible skin protection mechanism: the negative selection process of the skin environment to conditional pathogens. UHSG offers a convenient reference database that will facilitate a more in-depth understanding of the role of skin microorganisms in the skin.

An expectation-maximization algorithm for estimating proportions of deletions among bacterial populations with application to study antibiotic resistance gene transfer in Enterococcus faecalis.

The emergence of antibiotic resistance in bacteria limits the availability of antibiotic choices for treatment and infection control, thereby representing a major threat to human health. The de novo mutation of bacterial genomes is an essential mechanism by which bacteria acquire antibiotic resistance. Previously, deletion mutations within bacterial immune systems, ranging from dozens to thousands of base pairs (bps) in length, have been associated with the spread of antibiotic resistance. Most current methods for evaluating genomic structural variations (SVs) have concentrated on detecting them, rather than estimating the proportions of populations that carry distinct SVs. A better understanding of the distribution of mutations and subpopulations dynamics in bacterial populations is needed to appreciate antibiotic resistance evolution and movement of resistance genes through populations. Here, we propose a statistical model to estimate the proportions of genomic deletions in a mixed population based on Expectation-Maximization (EM) algorithms and next-generation sequencing (NGS) data. The method integrates both insert size and split-read mapping information to iteratively update estimated distributions. The proposed method was evaluated with three simulations that demonstrated the production of accurate estimations. The proposed method was then applied to investigate the horizontal transfers of antibiotic resistance genes in concert with changes in the CRISPR-Cas system of E. faecalis. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-022-00144-z.

Bacterial Pathogens: Potential Source For Antimicrobial Peptides.

As more antibiotics become ineffective due to drug-resistant bacteria, alternative therapies for infections must be prioritized. While pathogenic bacteria are a major threat, they also supply a massive reservoir of potential drugs for treating a wide range of illnesses. The concerning emergence of antimicrobial resistance and the rapidly dwindling therapeutic pipeline need the quick discovery and development of new antibiotics. Despite their great promise for natural product medicine development, pathogenic microorganisms have remained mostly unexplored and understudied. We review the antibacterial activity of specialized metabolites derived from pathogenic bacteria, emphasizing those presently in pre-clinical studies or with promise for medication development. Several atypical biosynthetic pathways are outlined, together with the crucial functions. We also discuss the mechanism of action and antibacterial activities of the antibiotics under consideration. Pathogenic bacteria as a rich source of antibiotics, along with recent advances in genomics and natural product research methods, may usher in a new golden age of antibiotic discovery.