Bacterial genomic epidemiology with mixed samples

Efficient and Robust Search of Microbial Genomes via Phylogenetic Compression

Comprehensive collections approaching millions of sequenced genomes have become central information sources in the life sciences. However, the rapid growth of these collections has made it effectively impossible to search these data using tools such as BLAST and its successors. Here, we present a technique called phylogenetic compression, which uses evolutionary history to guide compression and efficiently search large collections of microbial genomes using existing algorithms and data structures. We show that, when applied to modern diverse collections approaching millions of genomes, lossless phylogenetic compression improves the compression ratios of assemblies, de Bruijn graphs, and k -mer indexes by one to two orders of magnitude. Additionally, we develop a pipeline for a BLAST-like search over these phylogeny-compressed reference data, and demonstrate it can align genes, plasmids, or entire sequencing experiments against all sequenced bacteria until 2019 on ordinary desktop computers within a few hours. Phylogenetic compression has broad applications in computational biology and may provide a fundamental design principle for future genomics infrastructure.

What are the missing pieces needed to stop antibiotic resistance?

As recognized by several international agencies, antibiotic resistance is nowadays one of the most relevant problems for human health. While this problem was alleviated with the introduction of new antibiotics into the market in the golden age of antimicrobial discovery, nowadays few antibiotics are in the pipeline. Under these circumstances, a deep understanding on the mechanisms of emergence, evolution and transmission of antibiotic resistance, as well as on the consequences for the bacterial physiology of acquiring resistance is needed to implement novel strategies, beyond the development of new antibiotics or the restriction in the use of current ones, to more efficiently treat infections. There are still several aspects in the field of antibiotic resistance that are not fully understood. In the current article, we make a non-exhaustive critical review of some of them that we consider of special relevance, in the aim of presenting a snapshot of the studies that still need to be done to tackle antibiotic resistance.

Genetic strategies for sex-biased persistence of gut microbes across human life

Although compositional variation in the gut microbiome during human development has been extensively investigated, strain-resolved dynamic changes remain to be fully uncovered. In the current study, shotgun metagenomic sequencing data of 12,415 fecal microbiomes from healthy individuals are employed for strain-level tracking of gut microbiota members to elucidate its evolving biodiversity across the human life span. This detailed longitudinal meta-analysis reveals host sex-related persistence of strains belonging to common, maternally-inherited species, such as Bifidobacterium bifidum and Bifidobacterium longum subsp. longum. Comparative genome analyses, coupled with experiments including intimate interaction between microbes and human intestinal cells, show that specific bacterial glycosyl hydrolases related to host-glycan metabolism may contribute to more efficient colonization in females compared to males. These findings point to an intriguing ancient sex-specific host-microbe coevolution driving the selective persistence in women of key microbial taxa that may be vertically passed on to the next generation.

Extremely fast construction and querying of compacted and colored de Bruijn graphs with GGCAT

Compacted de Bruijn graphs are one of the most fundamental data structures in computational genomics. Colored compacted de Bruijn graphs are a variant built on a collection of sequences and associate to each k-mer the sequences in which it appears. We present GGCAT, a tool for constructing both types of graphs, based on a new approach merging the k-mer counting step with the unitig construction step, as well as on numerous practical optimizations. For compacted de Bruijn graph construction, GGCAT achieves speed-ups of 3× to 21× compared with the state-of-the-art tool Cuttlefish 2. When constructing the colored variant, GGCAT achieves speed-ups of 5× to 39× compared with the state-of-the-art tool BiFrost. Additionally, GGCAT is up to 480× faster than BiFrost for batch sequence queries on colored graphs.

Themisto: a scalable colored k-mer index for sensitive pseudoalignment against hundreds of thousands of bacterial genomes

MOTIVATION

Huge datasets containing whole-genome sequences of bacterial strains are now commonplace and represent a rich and important resource for modern genomic epidemiology and metagenomics. In order to efficiently make use of these datasets, efficient indexing data structures-that are both scalable and provide rapid query throughput-are paramount.

RESULTS

Here, we present Themisto, a scalable colored k-mer index designed for large collections of microbial reference genomes, that works for both short and long read data. Themisto indexes 179 thousand Salmonella enterica genomes in 9 h. The resulting index takes 142 gigabytes. In comparison, the best competing tools Metagraph and Bifrost were only able to index 11 000 genomes in the same time. In pseudoalignment, these other tools were either an order of magnitude slower than Themisto, or used an order of magnitude more memory. Themisto also offers superior pseudoalignment quality, achieving a higher recall than previous methods on Nanopore read sets.

AVAILABILITY AND IMPLEMENTATION

Themisto is available and documented as a C++ package at https://github.com/algbio/themisto available under the GPLv2 license.

Drivers of Resistance in Uganda and Malawi (DRUM): a protocol for the evaluation of One-Health drivers of Extended Spectrum Beta Lactamase (ESBL) resistance in Low-Middle Income Countries (LMICs)

In sub-Saharan Africa (sSA), there is high morbidity and mortality from severe bacterial infection and this is compounded by antimicrobial resistance, in particular, resistance to 3rd-generation cephalosporins. This resistance is typically mediated by extended-spectrum beta lactamases (ESBLs). To interrupt ESBL transmission it will be important to investigate how human behaviour, water, sanitation, and hygiene (WASH) practices, environmental contamination, and antibiotic usage in both urban and rural settings interact to contribute to transmission of ESBL E. coli and ESBL K. pneumoniae between humans, animals, and the environment. Here we present the protocol for the Drivers of Resistance in Uganda and Malawi (DRUM) Consortium, in which we will collect demographic, geospatial, clinical, animal husbandry and WASH data from a total of 400 households in Uganda and Malawi. Longitudinal human, animal and environmental sampling at each household will be used to isolate ESBL E. coli and ESBL K. pneumoniae. This will be complimented by a Risks, Attitudes, Norms, Abilities and Self-Regulation (RANAS) survey and structured observations to understand the contextual and psychosocial drivers of regional WASH practices. Bacterial isolates and plate sweeps will be further characterised using a mixture of short-,long-read and metagenomic whole-genome sequencing. These datasets will be integrated into agent-based models to describe the transmission of EBSL resistance in Uganda and Malawi and allow us to inform the design of interventions for interrupting transmission of ESBL-bacteria.

ASGARD+: A New Modular Platform for Bacterial Antibiotic-Resistant Analysis

ASGARD+ (Accelerated Sequential Genome-analysis and Antibiotic Resistance Detection) is a command-line platform for automatic identification of antibiotic-resistance genes in bacterial genomes, providing an easy-to-use interface to process big batches of sequence files from whole genome sequencing, with minimal configuration. It also provides a CPU-optimization algorithm that reduces the processing time. This tool consists of two main protocols. The first one, ASGARD, is based on the identification and annotation of antimicrobial resistance elements directly from the short reads using different public databases. SAGA, enables the alignment, indexing, and mapping of whole-genome samples against a reference genome for the detection and call of variants, as well as the visualization of the results through the construction of a tree of SNPs. The application of both protocols is performed using just one short command and one configuration file based on JSON syntax, which modulates each pipeline step, allowing the user to do as many interventions as needed on the different software tools that are adapted to the pipeline. The modular ASGARD+ allows researchers with little experience in bioinformatic analysis and command-line use to quickly explore bacterial genomes in depth, optimizing analysis times and obtaining accurate results. © 2023 Wiley Periodicals LLC. Basic Protocol 1: ASGARD+ installation Basic Protocol 2: Configuration files general setup Basic Protocol 3: ASGARD execution Support Protocol: Results visualization with Phandango Basic Protocol 4: SAGA execution Alternative Protocol 1: Container installation Alternative Protocol 2: Run ASGARD and SAGA in container.

Strong pathogen competition in neonatal gut colonisation

Opportunistic bacterial pathogen species and their strains that colonise the human gut are generally understood to compete against both each other and the commensal species colonising this ecosystem. Currently we are lacking a population-wide quantification of strain-level colonisation dynamics and the relationship of colonisation potential to prevalence in disease, and how ecological factors might be modulating these. Here, using a combination of latest high-resolution metagenomics and strain-level genomic epidemiology methods we performed a characterisation of the competition and colonisation dynamics for a longitudinal cohort of neonatal gut microbiomes. We found strong inter- and intra-species competition dynamics in the gut colonisation process, but also a number of synergistic relationships among several species belonging to genus Klebsiella, which includes the prominent human pathogen Klebsiella pneumoniae. No evidence of preferential colonisation by hospital-adapted pathogen lineages in either vaginal or caesarean section birth groups was detected. Our analysis further enabled unbiased assessment of strain-level colonisation potential of extra-intestinal pathogenic Escherichia coli (ExPEC) in comparison with their propensity to cause bloodstream infections. Our study highlights the importance of systematic surveillance of bacterial gut pathogens, not only from disease but also from carriage state, to better inform therapies and preventive medicine in the future.

Distribution and Current State of Molecular Genetic Characterization in Pathogenic Free-Living Amoebae

Free-living amoebae (FLA) are protozoa widely distributed in the environment, found in a great diversity of terrestrial biomes. Some genera of FLA are linked to human infections. The genus Acanthamoeba is currently classified into 23 genotypes (T1-T23), and of these some (T1, T2, T4, T5, T10, T12, and T18) are known to be capable of causing granulomatous amoebic encephalitis (GAE) mainly in immunocompromised patients while other genotypes (T2, T3, T4, T5, T6, T10, T11, T12, and T15) cause Acanthamoeba keratitis mainly in otherwise healthy patients. Meanwhile, Naegleria fowleri is the causative agent of an acute infection called primary amoebic meningoencephalitis (PAM), while Balamuthia mandrillaris, like some Acanthamoeba genotypes, causes GAE, differing from the latter in the description of numerous cases in patients immunocompetent. Finally, other FLA related to the pathologies mentioned above have been reported; Sappinia sp. is responsible for one case of amoebic encephalitis; Vermamoeba vermiformis has been found in cases of ocular damage, and its extraordinary capacity as endocytobiont for microorganisms of public health importance such as Legionella pneumophila, Bacillus anthracis, and Pseudomonas aeruginosa, among others. This review addressed issues related to epidemiology, updating their geographic distribution and cases reported in recent years for pathogenic FLA.

Combination of Whole Genome Sequencing and Metagenomics for Microbiological Diagnostics

Whole genome sequencing (WGS) provides the highest resolution for genome-based species identification and can provide insight into the antimicrobial resistance and virulence potential of a single microbiological isolate during the diagnostic process. In contrast, metagenomic sequencing allows the analysis of DNA segments from multiple microorganisms within a community, either using an amplicon- or shotgun-based approach. However, WGS and shotgun metagenomic data are rarely combined, although such an approach may generate additive or synergistic information, critical for, e.g., patient management, infection control, and pathogen surveillance. To produce a combined workflow with actionable outputs, we need to understand the pre-to-post analytical process of both technologies. This will require specific databases storing interlinked sequencing and metadata, and also involves customized bioinformatic analytical pipelines. This review article will provide an overview of the critical steps and potential clinical application of combining WGS and metagenomics together for microbiological diagnosis.

Drivers of Resistance in Uganda and Malawi (DRUM): a protocol for the evaluation of One-Health drivers of Extended Spectrum Beta Lactamase (ESBL) resistance in Low-Middle Income Countries (LMICs)

In sub-Saharan Africa (sSA), there is high morbidity and mortality from severe bacterial infection and this is compounded by antimicrobial resistance, in particular, resistance to 3rd-generation cephalosporins. This resistance is typically mediated by extended-spectrum beta lactamases (ESBLs). To interrupt ESBL transmission it will be important to investigate how human behaviour, water, sanitation, and hygiene (WASH) practices, environmental contamination, and antibiotic usage in both urban and rural settings interact to contribute to transmission of ESBL E. coli and ESBL K. pneumoniae between humans, animals, and the environment. Here we present the protocol for the Drivers of Resistance in Uganda and Malawi (DRUM) Consortium, in which we will collect demographic, geospatial, clinical, animal husbandry and WASH data from a total of 400 households in Uganda and Malawi. Longitudinal human, animal and environmental sampling at each household will be used to isolate ESBL E. coli and ESBL K. pneumoniae. This will be complimented by a Risks, Attitudes, Norms, Abilities and Self-Regulation (RANAS) survey and structured observations to understand the contextual and psychosocial drivers of regional WASH practices. Bacterial isolates and plate sweeps will be further characterised using a mixture of short-,long-read and metagenomic whole-genome sequencing. These datasets will be integrated into agent-based models to describe the transmission of EBSL resistance in Uganda and Malawi and allow us to inform the design of interventions for interrupting transmission of ESBL-bacteria.