Screening Host Genomic Data for Wolbachia Infections.

Less than a decade ago, the production of Wolbachia genomic assemblies was tedious, time-consuming, and expensive. The production of Wolbachia genomic DNA free of contamination from host DNA, as required for Wolbachia-targeted sequencing, was then only possible after the amplification and extraction of a large amount of clonal Wolbachia DNA. However, as an endosymbiotic bacterium, Wolbachia does not grow outside the host cell environment, and large-scale recovery of the bacteria required mass rearing of their host, preferably clones of a single individual to avoid strain genetic diversity, or amplification of cell cultures infected with a single Wolbachia strain. Bacterial DNA could be separated from host DNA based on genomic size. Nowadays, the production of full Wolbachia genomes does not require the physical isolation of the bacterial strains from their respective hosts, and the bacterium is often sequenced as a by-catch of host genomic projects. Here, we provide a step-by-step protocol to (1) identify whether host genome projects contain reads from associated Wolbachia and (2) isolate/retrieve the Wolbachia reads from the rest of the sequenced material. We hope this simple protocol will support many projects aiming at studying diverse Wolbachia genome assemblies.

A Worked Example of Screening Genomic Material for the Presence of Wolbachia Infection.

This chapter gives a brief overview of how to screen existing host genomic data for the presence of endosymbionts, such as Wolbachia. The various programs used provide test examples, and the corresponding manuals and discussion boards provide invaluable information. Please do consult these resources.

Identification of Protein Secretion Systems in Bacterial Genomes Using MacSyFinder Version 2.

Protein secretion systems are complex molecular machineries that translocate proteins through the outer membrane and sometimes through multiple other barriers. They have evolved by co-option of components from other envelope-associated cellular machineries, making them sometimes difficult to identify and discriminate. Here, we describe how to identify protein secretion systems in bacterial genomes using the MacSyFinder program. This flexible computational tool uses the knowledge gathered from experimental studies to identify homologous systems in genome data. It can be used with a set of predefined MacSyFinder models, "TXSScan," to identify all major secretion systems of diderm bacteria (i.e., with inner and LPS-containing outer membranes) as well as evolutionarily related cell appendages (pili and flagella). For this, it identifies and clusters co-localized genes encoding proteins of secretion systems using sequence similarity search with Hidden Markov Model (HMM) protein profiles. Finally, it checks if the clusters' genetic content and genomic organization satisfy the constraints of the model. TXSScan models can be altered in the command line or customized to search for variants of known secretion systems. Models can also be built from scratch to identify novel systems. In this chapter, we describe a complete pipeline of analysis, starting from (i) the integration of information from a reference set of experimentally studied systems, (ii) the identification of conserved proteins and the construction of their HMM protein profiles, (iii) the definition and optimization of "macsy-models," and (iv) their use and online distribution as tools to search genomic data for secretion systems of interest. MacSyFinder is available here: https://github.com/gem-pasteur/macsyfinder, and MacSyFinder models here: https://github.com/macsy-models .

Dancing the Nanopore limbo - Nanopore metagenomics from small DNA quantities for bacterial genome reconstruction.

BACKGROUND: While genome-resolved metagenomics has revolutionized our understanding of microbial and genetic diversity in environmental samples, assemblies of short-reads often result in incomplete and/or highly fragmented metagenome-assembled genomes (MAGs), hampering in-depth genomics. Although Nanopore sequencing has increasingly been used in microbial metagenomics as long reads greatly improve the assembly quality of MAGs, the recommended DNA quantity usually exceeds the recoverable amount of DNA of environmental samples. Here, we evaluated lower-than-recommended DNA quantities for Nanopore library preparation by determining sequencing quality, community composition, assembly quality and recovery of MAGs. RESULTS: We generated 27 Nanopore metagenomes using the commercially available ZYMO mock community and varied the amount of input DNA from 1000 ng (the recommended minimum) down to 1 ng in eight steps. The quality of the generated reads remained stable across all input levels. The read mapping accuracy, which reflects how well the reads match a known reference genome, was consistently high across all libraries. The relative abundance of the species in the metagenomes was stable down to input levels of 50 ng. High-quality MAGs (> 95% completeness, ≤ 5% contamination) could be recovered from metagenomes down to 35 ng of input material. When combined with publicly available Illumina reads for the mock community, Nanopore reads from input quantities as low as 1 ng improved the quality of hybrid assemblies. CONCLUSION: Our results show that the recommended DNA amount for Nanopore library preparation can be substantially reduced without any adverse effects to genome recovery and still bolster hybrid assemblies when combined with short-read data. We posit that the results presented herein will enable studies to improve genome recovery from low-biomass environments, enhancing microbiome understanding.

Snapper: high-sensitive detection of methylation motifs based on Oxford Nanopore reads.

MOTIVATION: The Oxford Nanopore technology has a great potential for the analysis of methylated motifs in genomes, including whole-genome methylome profiling. However, we found that there are no methylation motifs detection algorithms, which would be sensitive enough and return deterministic results. Thus, the MEME suit does not extract all Helicobacter pylori methylation sites de novo even using the iterative approach implemented in the most up-to-date methylation analysis tool Nanodisco. RESULTS: We present Snapper, a new highly sensitive approach, to extract methylation motif sequences based on a greedy motif selection algorithm. Snapper does not require manual control during the enrichment process and has enrichment sensitivity higher than MEME coupled with Tombo or Nanodisco instruments that was demonstrated on H.pylori strain J99 studied earlier by the PacBio technology and on four external datasets representing different bacterial species. We used Snapper to characterize the total methylome of a new H.pylori strain A45. At least four methylation sites that have not been described for H.pylori earlier were revealed. We experimentally confirmed the presence of a new CCAG-specific methyltransferase and inferred a gene encoding a new CCAAK-specific methyltransferase. AVAILABILITY AND IMPLEMENTATION: Snapper is implemented using Python and is freely available as a pip package named "snapper-ont." Also, Snapper and the demo dataset are available in Zenodo (10.5281/zenodo.10117651).

Introduction and benchmarking of pyMLST: open-source software for assessing bacterial clonality using core genome MLST.

Core genome multilocus sequence typing (cgMLST) has gained in popularity for bacterial typing since whole-genome sequencing (WGS) has become affordable. We introduce here pyMLST, a new complete, stand-alone, free and open source pipeline for cgMLST analysis. pyMLST can create or import a core genome database. For each gene, the first allele is aligned against the bacterial genome of interest using BLAT. Incomplete genes are aligned using MAFT. All data are stored in a SQLite database. pyMLST accepts assembly genomes or raw data (with the option pyMLST-KMA) as input. To evaluate our new tool, we selected three genome collections of major bacterial pathogens (Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus) and compared them with pyMLST, pyMLST-KMA, ChewBBACA, SeqSphere and the variant calling approach. We compared the sensitivity, precision and false-positive rate for each method with those of the variant calling approach. Minimal spanning trees were generated with each type of software to evaluate their interest in the context of a bacterial outbreak. We found that pyMLST-KMA is a convenient screening method to avoid assembling large bacterial collections. Our data showed that pyMLST (free, open source, available in Galaxy and pipeline ready) performed similarly to the commercial SeqSphere and performed better than ChewBBACA and pyMLST-KMA.

Systematic analysis of plasmids of the Serratia marcescens complex using 142 closed genomes.

Plasmids play important roles in bacterial genome diversification. In the Serratia marcescens complex (SMC), a notable contribution of plasmids to genome diversification was also suggested by our recent analysis of >600 draft genomes. As accurate analyses of plasmids in draft genomes are difficult, in this study we analysed 142 closed genomes covering the entire complex, 67 of which were obtained in this study, and identified 132 plasmids (1.9-244.4 kb in length) in 77 strains. While the average numbers of plasmids in clinical and non-clinical strains showed no significant difference, strains belonging to clade 2 (one of the two hospital-adapted lineages) contained more plasmids than the others. Pangenome analysis revealed that of the 28 954 genes identified, 12.8 % were plasmid-specific, and 1.4 % were present in plasmids or chromosomes depending on the strain. In the latter group, while transposon-related genes were most prevalent (31.4 % of the function-predicted genes), genes related to antimicrobial resistance and heavy metal resistance accounted for a notable proportion (22.7 %). Mash distance-based clustering separated the 132 plasmids into 23 clusters and 50 singletons. Most clusters/singletons showed notably different GC contents compared to those of host chromosomes, suggesting their recent or relatively recent appearance in the SMC. Among the 23 clusters, 17 were found in only clinical or only non-clinical strains, suggesting the possible preference of their distribution on the environmental niches of host strains. Regarding the host strain phylogeny, 16 clusters were distributed in two or more clades, suggesting their interclade transmission. Moreover, for many plasmids, highly homologous plasmids were found in other species, indicating the broadness of their potential host ranges, beyond the genus, family, order, class or even phylum level. Importantly, highly homologous plasmids were most frequently found in Klebsiella pneumoniae and other species in the family Enterobacteriaceae, suggesting that this family, particularly K. pneumoniae, is the main source for plasmid exchanges with the SMC. These results highlight the power of closed genome-based analysis in the investigation of plasmids and provide important insights into the nature of plasmids distributed in the SMC.

Delving into the lifestyle of Sundarban Wetland resident, biofilm producing, halotolerant Salinicoccus roseus: a comparative genomics-based intervention.

BACKGROUND: Microbial community played an essential role in ecosystem processes, be it mangrove wetland or other intertidal ecologies. Several enzymatic activities like hydrolases are effective ecological indicators of soil microbial function. So far, little is known on halophilic bacterial contribution and function on a genomic viewpoint of Indian Sundarban Wetland. Considering the above mentioned issues, the aims of this study was to understand the life style, metabolic functionalities and genomic features of the isolated bacterium, Salinicoccus roseus strain RF1H. A comparative genome-based study of S. roseus has not been reported yet. Henceforth, we have considered the inclusion of the intra-species genome comparison of S. roseus to gain insight into the high degree of variation in the genome of strain RF1H among others. RESULTS: Salinicoccus roseus strain RF1H is a pink-red pigmented, Gram-positive and non-motile cocci. The bacterium exhibited high salt tolerance (up to 15% NaCl), antibiotic resistance, biofilm formation and secretion of extracellular hydrolytic enzymes. The circular genome was approximately 2.62978 Mb in size, encoding 574 predicted genes with GC content 49.5%. Presence of genomic elements (prophages, transposable elements, CRISPR-Cas system) represented bacterial virulence and multidrug-resistance. Furthermore, genes associated with salt tolerance, temperature adaptation and DNA repair system were distributed in 17 genomic islands. Genes related to hydrocarbon degradation manifested metabolic capability of the bacterium for potential biotechnological applications. A comparative pangenome analysis revealed two-component response regulator, modified C4-dicarboxylate transport system and osmotic stress regulated ATP-binding proteins. Presence of genes encoding arginine decarboxylase (ADC) enzyme being involved in biofilm formation was reported from the genome. In silico study revealed the protein is thermostable and made up with ~ 415 amino acids, and hydrophilic in nature. Three motifs appeared to be evolutionary conserved in all Salinicoccus sequences. CONCLUSION: The first report of whole genome analysis of Salinicoccus roseus strain RF1H provided information of metabolic functionalities, biofilm formation, resistance mechanism and adaptation strategies to thrive in climate-change induced vulnerable spot like Sundarban. Comparative genome analysis highlighted the unique genome content that contributed the strain's adaptability. The biomolecules produced during metabolism are important sources of compounds with potential beneficial applications in pharmaceuticals.

Distributed genotyping and clustering of Neisseria strains reveal continual emergence of epidemic meningococcus over a century.

Core genome multilocus sequence typing (cgMLST) is commonly used to classify bacterial strains into different types, for taxonomical and epidemiological applications. However, cgMLST schemes require central databases for the nomenclature of new alleles and sequence types, which must be synchronized worldwide and involve increasingly intensive calculation and storage demands. Here, we describe a distributed cgMLST (dcgMLST) scheme that does not require a central database of allelic sequences and apply it to study evolutionary patterns of epidemic and endemic strains of the genus Neisseria. We classify 69,994 worldwide Neisseria strains into multi-level clusters that assign species, lineages, and local disease outbreaks. We divide Neisseria meningitidis into 168 endemic lineages and three epidemic lineages responsible for at least 9 epidemics in the past century. According to our analyses, the epidemic and endemic lineages experienced very different population dynamics in the past 100 years. Epidemic lineages repetitively emerged from endemic lineages, disseminated worldwide, and apparently disappeared rapidly afterward. We propose a stepwise model for the evolutionary trajectory of epidemic lineages in Neisseria, and expect that the development of similar dcgMLST schemes will facilitate epidemiological studies of other bacterial pathogens.

Association between two-component systems gene mutation and Mycobacterium tuberculosis transmission revealed by whole genome sequencing.

BACKGROUND: Two-component systems (TCSs) assume a pivotal function in Mycobacterium tuberculosis (M.tuberculosis) growth. However, the exact regulatory mechanism of this system needs to be elucidated, and only a few studies have investigated the effect of gene mutations within TCSs on M.tuberculosis transmission. This research explored the relationship between TCSs gene mutation and the global transmission of (M.tuberculosis). RESULTS: A total of 13531 M.tuberculosis strains were enrolled in the study. Most of the M.tuberculosis strains belonged to lineage4 (n=6497,48.0%), followed by lineage2 (n=5136,38.0%). Our results showed that a total of 36 single nucleotide polymorphisms (SNPs) were positively correlated with clustering of lineage2, such as Rv0758 (phoR, C820G), Rv1747(T1102C), and Rv1057(C1168T). A total of 30 SNPs showed positive correlation with clustering of lineage4, such as phoR(C182A, C1184G, C662T, T758G), Rv3764c (tcrY, G1151T), and Rv1747 C20T. A total of 19 SNPs were positively correlated with cross-country transmission of lineage2, such as phoR A575C, Rv1028c (kdpD, G383T, G1246C), and Rv1057 G817T. A total of 41 SNPs were positively correlated with cross-country transmission of lineage4, such as phoR(T758G, T327G, C284G), kdpD(G1755A, G625C), Rv1057 C980T, and Rv1747 T373G. CONCLUSIONS: Our study identified that SNPs in genes of two-component systems were related to the transmission of M. tuberculosis. This finding adds another layer of complexity to M. tuberculosis virulence and provides insight into future research that will help to elucidate a novel mechanism of M. tuberculosis pathogenicity.

RabbitKSSD: accelerating genome distance estimation on modern multi-core architectures.

SUMMARY: We propose RabbitKSSD, a high-speed genome distance estimation tool. Specifically, we leverage load-balanced task partitioning, fast I/O, efficient intermediate result accesses, and high-performance data structures to improve overall efficiency. Our performance evaluation demonstrates that RabbitKSSD achieves speedups ranging from 5.7× to 19.8× over Kssd for the time-consuming sketch generation and distance computation on commonly used workstations. In addition, it significantly outperforms Mash, BinDash, and Dashing2. Moreover, RabbitKSSD can efficiently perform all-vs-all distance computation for all RefSeq complete bacterial genomes (455 GB in FASTA format) in just 2 min on a 64-core workstation. AVAILABILITY AND IMPLEMENTATION: RabbitKSSD is available at https://github.com/RabbitBio/RabbitKSSD.

Genome mining reveals novel biosynthetic gene clusters in entomopathogenic bacteria.

The discovery of novel bioactive compounds produced by microorganisms holds significant potential for the development of therapeutics and agrochemicals. In this study, we conducted genome mining to explore the biosynthetic potential of entomopathogenic bacteria belonging to the genera Xenorhabdus and Photorhabdus. By utilizing next-generation sequencing and bioinformatics tools, we identified novel biosynthetic gene clusters (BGCs) in the genomes of the bacteria, specifically plu00736 and plu00747. These clusters were identified as unidentified non-ribosomal peptide synthetase (NRPS) and unidentified type I polyketide synthase (T1PKS) clusters. These BGCs exhibited unique genetic architecture and encoded several putative enzymes and regulatory elements, suggesting its involvement in the synthesis of bioactive secondary metabolites. Furthermore, comparative genome analysis revealed that these BGCs were distinct from previously characterized gene clusters, indicating the potential for the production of novel compounds. Our findings highlighted the importance of genome mining as a powerful approach for the discovery of biosynthetic gene clusters and the identification of novel bioactive compounds. Further investigations involving expression studies and functional characterization of the identified BGCs will provide valuable insights into the biosynthesis and potential applications of these bioactive compounds.

Genomic analysis of a marine alphaproteobacterium Sagittula sp. strain MA-2 that carried eight plasmids.

Bacteria that belong to the family Roseobacteraceae in the Alphaproteobacteria class are widely distributed in marine environments with remarkable physiological diversity, which is considered to be attributed to their genomic plasticity. In this study, a novel isolate of the genus Sagittula within Roseobacteraceae, strain MA-2, was obtained from a coastal marine bacterial consortium enriched with aromatic hydrocarbons, and its complete genome was sequenced. The genome with a total size of 5.69 Mbp was revealed to consist of a 4.67-Mbp circular chromosome and eight circular plasmids ranging in size from 19.5 to 361.5 kbp. Further analyses of functional genes in the strain MA-2 genome identified homologous genes responsible for the biotransformation of gentisic acid, which were located on one of its plasmids and were not found in genomes of other Sagittula strains available from databases. This suggested that strain MA-2 had acquired these genes via horizontal gene transfers that enabled them to degrade and utilize gentisic acid as a growth substrate. This study provided the second complete genome sequence of the genus Sagittula and supports the hypothesis that acquisition of ecologically relevant genes in extrachromosomal replicons allows Roseobacteraceae to be highly adaptable to diverse lifestyles.

The complete genome sequence of Peribacillus sp. R9-11 for genome mining of polystyrene degrading enzymes.

Peribacillus sp. R9-11, isolated from a marine sediment sample of the Arctic Ocean, can grow in mineral medium with polystyrene (PS) plastic as sole carbon source. Here, we present the complete genome of Peribacillus sp. R9-11, which will facilitate the genome mining of PS degrading enzymes. The total length of the sequenced genome consists of 6,288,471 bases, with mean G + C content of 37.93%. A total of 6447 coding genes including 84 tRNAs and 37 rRNAs were predicted in the genome. Some potential PS degrading enzymes including cytochrome P450s and peroxidases were found in this genome.

VBCG: 20 validated bacterial core genes for phylogenomic analysis with high fidelity and resolution.

BACKGROUND: Phylogenomic analysis has become an inseparable part of studies of bacterial diversity and evolution, and many different bacterial core genes have been collated and used for phylogenomic tree reconstruction. However, these genes have been selected based on their presence and single-copy ratio in all bacterial genomes, leaving out the gene's 'phylogenetic fidelity' unexamined. RESULTS: From 30,522 complete genomes covering 11,262 species, we examined 148 bacterial core genes that have been previously used for phylogenomic analysis. In addition to the gene presence and single-copy rations, we evaluated the gene's phylogenetic fidelity by comparing each gene's phylogeny with its corresponding 16S rRNA gene tree. Out of the 148 bacterial genes, 20 validated bacterial core genes (VBCG) were selected as the core gene set with the highest bacterial phylogenetic fidelity. Compared to the larger gene set, the 20-gene core set resulted in more species having all genes present and fewer species with missing data, thereby enhancing the accuracy of phylogenomic analysis. Using Escherichia coli strains as examples of prominent bacterial foodborne pathogens, we demonstrated that the 20 VBCG produced phylogenies with higher fidelity and resolution at species and strain levels while 16S rRNA gene tree alone could not. CONCLUSION: The 20 validated core gene set improves the fidelity and speed of phylogenomic analysis. Among other uses, this tool improves our ability to explore the evolution, typing and tracking of bacterial strains, such as human pathogens. We have developed a Python pipeline and a desktop graphic app (available on GitHub) for users to perform phylogenomic analysis with high fidelity and resolution. Video Abstract.

Taxonomic and environmental distribution of bacterial amino acid auxotrophies.

Many microorganisms are auxotrophic-unable to synthesize the compounds they require for growth. With this work, we quantify the prevalence of amino acid auxotrophies across a broad diversity of bacteria and habitats. We predicted the amino acid biosynthetic capabilities of 26,277 unique bacterial genomes spanning 12 phyla using a metabolic pathway model validated with empirical data. Amino acid auxotrophy is widespread across bacterial phyla, but we conservatively estimate that the majority of taxa (78.4%) are able to synthesize all amino acids. Our estimates indicate that amino acid auxotrophies are more prevalent among obligate intracellular parasites and in free-living taxa with genomic attributes characteristic of 'streamlined' life history strategies. We predicted the amino acid biosynthetic capabilities of bacterial communities found in 12 unique habitats to investigate environmental associations with auxotrophy, using data compiled from 3813 samples spanning major aquatic, terrestrial, and engineered environments. Auxotrophic taxa were more abundant in host-associated environments (including the human oral cavity and gut) and in fermented food products, with auxotrophic taxa being relatively rare in soil and aquatic systems. Overall, this work contributes to a more complete understanding of amino acid auxotrophy across the bacterial tree of life and the ecological contexts in which auxotrophy can be a successful strategy.

Draft genomes of novel avian Chlamydia abortus strains from Australian Torresian crows (Corvus orru) shed light on possible reservoir hosts and evolutionary pathways.

Chlamydia abortus, an obligate intracellular bacterium, is a major causative agent of reproductive loss in ruminants, with zoonotic potential. Though this pathogen is primarily known to infect livestock, recent studies have detected and isolated genetically distinct avian strains of C. abortus from wild birds globally. Before this study, only five avian C. abortus genomes were publicly available. Therefore, we performed culture-independent probe-based whole-genome sequencing on clinical swabs positive for avian C. abortus obtained from Australian Torresian crows (Corvus orru) in 2019 and 2020. We successfully obtained draft genomes for three avian C. abortus strains (C1, C2 and C3), each comprising draft chromosomes with lengths of 1 115 667, 1 120 231 and 1 082 115 bp, and associated 7 553 bp plasmids, with a genome completeness exceeding 92 %. Molecular characterization revealed that these three strains comprise a novel sequence type (ST333), whilst phylogenetic analyses placed all three strains in a cluster with other avian C. abortus genomes. Interestingly, these three strains share a distant genomic relation (2693 single nucleotide variants) with the reference strain 15-58d/44 (ST152), isolated from a Eurasian magpie (Pica pica) in Poland, highlighting the need for more publicly available genomes. Broad comparative analyses with other avian C. abortus genomes revealed that the three draft genomes contain conserved Chlamydia genomic features, including genes coding for type III secretion system and polymorphic membrane proteins, and potential virulence factors such as the large chlamydial cytotoxin, warranting further studies. This research provides the first avian C. abortus draft genomes from Australian birds, highlighting Torresian crows as novel reservoir hosts for these potential pathogens, and demonstrates a practical methodology for sequencing novel Chlamydia genomes without relying on traditional cell culture.

Reduced ambiguity and improved interpretability of bacterial genome-wide associations using gene-cluster-centric k-mers.

The wide adoption of bacterial genome sequencing and encoding both core and accessory genome variation using k-mers has allowed bacterial genome-wide association studies (GWAS) to identify genetic variants associated with relevant phenotypes such as those linked to infection. Significant limitations still remain because of k-mers being duplicated across gene clusters and as far as the interpretation of association results is concerned, which affects the wider adoption of GWAS methods on microbial data sets. We have developed a simple computational method (panfeed) that explicitly links each k-mer to their gene cluster at base-resolution level, which allows us to avoid biases introduced by a global de Bruijn graph as well as more easily map and annotate associated variants. We tested panfeed on two independent data sets, correctly identifying previously characterized causal variants, which demonstrates the precision of the method, as well as its scalable performance. panfeed is a command line tool written in the python programming language and is available at https://github.com/microbial-pangenomes-lab/panfeed.

Bacterial genome size and gene functional diversity negatively correlate with taxonomic diversity along a pH gradient.

Bacterial gene repertoires reflect adaptive strategies, contribute to ecosystem functioning and are limited by genome size. However, gene functional diversity does not necessarily correlate with taxonomic diversity because average genome size may vary by community. Here, we analyse gene functional diversity (by shotgun metagenomics) and taxonomic diversity (by 16S rRNA gene amplicon sequencing) to investigate soil bacterial communities along a natural pH gradient in 12 tropical, subtropical, and temperate forests. We find that bacterial average genome size and gene functional diversity decrease, whereas taxonomic diversity increases, as soil pH rises from acid to neutral; as a result, bacterial taxonomic and functional diversity are negatively correlated. The gene repertoire of acid-adapted oligotrophs is enriched in functions of signal transduction, cell motility, secretion system, and degradation of complex compounds, while that of neutral pH-adapted copiotrophs is enriched in functions of energy metabolism and membrane transport. Our results indicate that a mismatch between taxonomic and functional diversity can arise when environmental factors (such as pH) select for adaptive strategies that affect genome size distributions.

Evaluation of Fourier transform-infrared spectroscopy (FT-IR) as a control measure for nosocomial outbreak investigations.

Whole-genome sequencing (WGS) provides greater resolution than other molecular epidemiology strategies and is emerging as a new gold standard approach for microbial strain typing. The Bruker IR Biotyper is designed as a screening tool to identify bacterial isolates that require WGS to establish accurate relationships, but its performance and utility in nosocomial outbreak investigations have not been thoroughly investigated. Here, we evaluated the IR Biotyper by retrospectively examining isolates tested by WGS during investigations of potential nosocomial transmission events or outbreaks. Ninety-eight clinical isolates from 14 different outbreak investigations were examined: three collections of Acinetobacter baumannii (n = 2, n = 9, n = 5 isolates in each collection), one of Escherichia coli (n = 16), two of Pseudomonas aeruginosa (n = 2 and n = 5), two of Serratia marcescens (n = 9 and n = 7), five of Staphylococcus aureus (n = 8, n = 4, n = 3, n = 3, n = 17), and one of Stenotrophomonas maltophilia (n = 8). Linear regression demonstrated a weak, positive correlation between the number of pairwise genome-wide single-nucleotide polymorphisms (SNPs) and IR Biotyper spectral distance values for Gram-positive (r = 0.43, P ≤ 0.0001), Gram-negative (r = 0.1554, P = 0.0639), and all organisms combined (r = 0.342, P ≤ 0.0001). Overall, the IR Biotyper had a positive predictive value (PPV) of 55.81% for identifying strains that were closely related by genomic identity, but a negative predictive value (NPV) of 86.79% for identifying unrelated isolates. When experimentally adjusted cut-offs were applied to A. baumannii, P. aeruginosa, and E. coli, the PPV was 62% for identifying strains that were closely related and the NPV was 100% for identifying unrelated isolates. Implementation of the IR Biotyper as a screening tool in this cohort would have reduced the number of Gram-negative isolates requiring further WGS analysis by 50% and would reduce the number of S. aureus isolates needing WGS resolution by 48%.