StrainGE: a toolkit to track and characterize low-abundance strains in complex microbial communities

Transient colonizing microbes promote gut dysbiosis and functional impairment

Species composition of the healthy adult gut microbiota tends to be stable over time. Destabilization of the gut microbiome under the influence of different factors is the main driver of the microbial dysbiosis and subsequent impacts on host physiology. Here, we used metagenomics data from a Swedish longitudinal cohort, to determine the stability of the gut microbiome and uncovered two distinct microbial species groups; persistent colonizing species (PCS) and transient colonizing species (TCS). We validated the continuation of this grouping, generating gut metagenomics data for additional time points from the same Swedish cohort. We evaluated the existence of PCS/TCS across different geographical regions and observed they are globally conserved features. To characterize PCS/TCS phenotypes, we performed bioreactor fermentation with faecal samples and metabolic modeling. Finally, using chronic disease gut metagenome and other multi-omics data, we identified roles of TCS in microbial dysbiosis and link with abnormal changes to host physiology.

Bacterial strain sharing between humans, animals, and the environment among urban households

Identifying bacterial transmission pathways is crucial to inform strategies aimed at curbing the spread of pathogenic and antibiotic-resistant bacteria, especially in rapidly urbanizing low- and middle-income countries. In this study, we assessed bacterial strain-sharing and dissemination of antibiotic resistance across humans, domesticated poultry, canines, household soil, and drinking water in urban informal settlements in Nairobi, Kenya. We collected 321 samples from 50 households and performed Pooling Isolated Colonies-seq (PIC-seq) by sequencing pools of up to five Escherichia coli colonies per sample to capture strain diversity, strain-sharing patterns, and overlap of antibiotic-resistant genes (ARGs). Bacterial strains isolated from the household environment carried clinically relevant ARGs, reinforcing the role of the environment in antibiotic resistance dissemination. Strain-sharing rates and resistome similarities across sample types were strongly correlated within households, suggesting clonal spread of bacteria is a main driver of dissemination of ARGs in the domestic urban environment. Within households, E. coli strain-sharing was rare between humans and animals but more frequent between humans and drinking water. E. coli contamination in stored drinking water was also associated with higher strain-sharing between humans in the same household. Our study demonstrates that contaminated drinking water facilitates human to human strain sharing and water treatment can disrupt transmission.

Combined metagenomic- and culture-based approaches to investigate bacterial strain-level associations with medication-controlled mild-moderate atopic dermatitis

Background

The skin microbiome is disrupted in atopic dermatitis (AD). Existing research focuses on moderate to severe, unmedicated disease.

Objective

We sought to investigate metagenomic- and culture-based bacterial strain-level differences in mild, medicated AD and the effects these have on human keratinocytes (HKs).

Methods

Skin swabs from anterior forearms were collected from 20 pediatric participants (11 participants with AD sampled at lesional and nonlesional sites and 9 age- and sex-matched controls). Participants had primarily mild to moderate AD and maintained medication use. Samples were processed for microbial metagenomic sequencing and bacterial isolation. Isolates identified as Staphylococcus aureus were tested for enterotoxin production. HK cultures were treated with cell-free conditioned media from representative Staphylococcus species to measure barrier effects.

Results

Metagenomic sequencing identified significant differences in microbiome composition between AD and control groups. Differences were seen at the species and strain levels for Staphylococci, with S aureus found only in participants with AD and differences in Staphylococcus epidermidis strains between control and AD swabs. These strains showed differences in toxin gene presence, which was confirmed in vitro for S aureus enterotoxins. The strain from the participant with the most severe AD produced enterotoxin B levels more than 100-fold higher than the other strains (P < .001). Strains also displayed differential effects on HK metabolism and barrier function.

Conclusions

Strain-level differences in toxin genes from Staphylococcus strains may explain varying effects on HK, with S aureus and non-aureus strains negatively affecting viability and barrier function. These differences are likely important in AD pathogenesis.

Floria: fast and accurate strain haplotyping in metagenomes

SUMMARY

Shotgun metagenomics allows for direct analysis of microbial community genetics, but scalable computational methods for the recovery of bacterial strain genomes from microbiomes remains a key challenge. We introduce Floria, a novel method designed for rapid and accurate recovery of strain haplotypes from short and long-read metagenome sequencing data, based on minimum error correction (MEC) read clustering and a strain-preserving network flow model. Floria can function as a standalone haplotyping method, outputting alleles and reads that co-occur on the same strain, as well as an end-to-end read-to-assembly pipeline (Floria-PL) for strain-level assembly. Benchmarking evaluations on synthetic metagenomes show that Floria is  > 3× faster and recovers 21% more strain content than base-level assembly methods (Strainberry) while being over an order of magnitude faster when only phasing is required. Applying Floria to a set of 109 deeply sequenced nanopore metagenomes took <20 min on average per sample and identified several species that have consistent strain heterogeneity. Applying Floria's short-read haplotyping to a longitudinal gut metagenomics dataset revealed a dynamic multi-strain Anaerostipes hadrus community with frequent strain loss and emergence events over 636 days. With Floria, accurate haplotyping of metagenomic datasets takes mere minutes on standard workstations, paving the way for extensive strain-level metagenomic analyses.

AVAILABILITY AND IMPLEMENTATION

Floria is available at https://github.com/bluenote-1577/floria, and the Floria-PL pipeline is available at https://github.com/jsgounot/Floria_analysis_workflow along with code for reproducing the benchmarks.

First parechovirus reported case in Saudi Arabia in hospitalized immunocompromised adult patient

Human parechovirus, a member of the Picornaviridae family (PeVs), can lead to severe infections, including severe meningitis, meningoencephalitis, and sepsis-like syndrome. We report a case of human parechovirus-related encephalitis in a 52-year-old woman diagnosed with glioblastoma multiforme. She underwent surgical resection in June 2022. Unfortunately, her disease recurred, and she underwent a second resection in August 2022, followed by radiation therapy and Temozolomide therapy. She presented to the hospital with acute confusion followed by seizures, necessitating intubation for airway support. A cerebrospinal fluid (CSF) sample was obtained and processed using the Biofire FilmArray, which reported the detection of HSV-1. Despite being on Acyclovir, the patient did not show signs of improvement. Consequently, a second CSF sample was obtained and sent for next-generation sequencing (NGS), which returned a positive result for Parechovirus. In this presented case, the patient exhibited symptoms of an unknown infectious cause. The utilization of NGS and metagenomic analysis helped identify Parechovirus as the primary pathogen present, in addition to previously identified HSV. This comprehensive approach facilitated a thorough assessment of the underlying infection and guided targeted treatment. In conclusion, the application of NGS techniques and metagenomic analysis proved instrumental in identifying the root cause of the infection.

Mora: abundance aware metagenomic read re-assignment for disentangling similar strains

BACKGROUND

Taxonomic classification of reads obtained by metagenomic sequencing is often a first step for understanding a microbial community, but correctly assigning sequencing reads to the strain or sub-species level has remained a challenging computational problem.

RESULTS

We introduce Mora, a MetagenOmic read Re-Assignment algorithm capable of assigning short and long metagenomic reads with high precision, even at the strain level. Mora is able to accurately re-assign reads by first estimating abundances through an expectation-maximization algorithm and then utilizing abundance information to re-assign query reads. The key idea behind Mora is to maximize read re-assignment qualities while simultaneously minimizing the difference from estimated abundance levels, allowing Mora to avoid over assigning reads to the same genomes. On simulated diverse reads, this allows Mora to achieve F1 scores comparable to other algorithms while having less runtime. However, Mora significantly outshines other algorithms on very similar reads. We show that the high penalty of over assigning reads to a common reference genome allows Mora to accurately infer correct strains for real data in the form of E. coli reads.

CONCLUSIONS

Mora is a fast and accurate read re-assignment algorithm that is modularized, allowing it to be incorporated into general metagenomics and genomics workflows. It is freely available at https://github.com/AfZheng126/MORA .

Phage predation, disease severity, and pathogen genetic diversity in cholera patients

Despite an increasingly detailed picture of the molecular mechanisms of bacteriophage (phage)-bacterial interactions, we lack an understanding of how these interactions evolve and impact disease within patients. In this work, we report a year-long, nationwide study of diarrheal disease patients in Bangladesh. Among cholera patients, we quantified Vibrio cholerae (prey) and its virulent phages (predators) using metagenomics and quantitative polymerase chain reaction while accounting for antibiotic exposure using quantitative mass spectrometry. Virulent phage (ICP1) and antibiotics suppressed V. cholerae to varying degrees and were inversely associated with severe dehydration depending on resistance mechanisms. In the absence of antiphage defenses, predation was "effective," with a high predator:prey ratio that correlated with increased genetic diversity among the prey. In the presence of antiphage defenses, predation was "ineffective," with a lower predator:prey ratio that correlated with increased genetic diversity among the predators. Phage-bacteria coevolution within patients should therefore be considered in the deployment of phage-based therapies and diagnostics.

High-risk Escherichia coli clones that cause neonatal meningitis and association with recrudescent infection

Neonatal meningitis is a devastating disease associated with high mortality and neurological sequelae. Escherichia coli is the second most common cause of neonatal meningitis in full-term infants (herein NMEC) and the most common cause of meningitis in preterm neonates. Here, we investigated the genomic relatedness of a collection of 58 NMEC isolates spanning 1974-2020 and isolated from seven different geographic regions. We show NMEC are comprised of diverse sequence types (STs), with ST95 (34.5%) and ST1193 (15.5%) the most common. No single virulence gene profile was conserved in all isolates; however, genes encoding fimbrial adhesins, iron acquisition systems, the K1 capsule, and O antigen types O18, O75, and O2 were most prevalent. Antibiotic resistance genes occurred infrequently in our collection. We also monitored the infection dynamics in three patients that suffered recrudescent invasive infection caused by the original infecting isolate despite appropriate antibiotic treatment based on antibiogram profile and resistance genotype. These patients exhibited severe gut dysbiosis. In one patient, the causative NMEC isolate was also detected in the fecal flora at the time of the second infection episode and after treatment. Thus, although antibiotics are the standard of care for NMEC treatment, our data suggest that failure to eliminate the causative NMEC that resides intestinally can lead to the existence of a refractory reservoir that may seed recrudescent infection.

Phage predation, disease severity and pathogen genetic diversity in cholera patients

Despite an increasingly detailed picture of the molecular mechanisms of phage-bacterial interactions, we lack an understanding of how these interactions evolve and impact disease within patients. Here we report a year-long, nation-wide study of diarrheal disease patients in Bangladesh. Among cholera patients, we quantified Vibrio cholerae (prey) and its virulent phages (predators) using metagenomics and quantitative PCR, while accounting for antibiotic exposure using quantitative mass spectrometry. Virulent phage (ICP1) and antibiotics suppressed V. cholerae to varying degrees and were inversely associated with severe dehydration depending on resistance mechanisms. In the absence of anti-phage defenses, predation was 'effective,' with a high predator:prey ratio that correlated with increased genetic diversity among the prey. In the presence of anti-phage defenses, predation was 'ineffective,' with a lower predator:prey ratio that correlated with increased genetic diversity among the predators. Phage-bacteria coevolution within patients should therefore be considered in the deployment of phage-based therapies and diagnostics.

A user's guide to the bioinformatic analysis of shotgun metagenomic sequence data for bacterial pathogen detection

Metagenomics, i.e., shotgun sequencing of the total microbial community DNA from a sample, has become a mature technique but its application to pathogen detection in clinical, environmental, and food samples is far from common or standardized. In this review, we summarize ongoing developments in metagenomic sequence analysis that facilitate its wider application to pathogen detection. We examine theoretical frameworks for estimating the limit of detection for a particular level of sequencing effort, current approaches for achieving species and strain analytical resolution, and discuss some relevant modern tools for these tasks. While these recent advances are significant and establish metagenomics as a powerful tool to provide insights not easily attained by culture-based approaches, metagenomics is unlikely to emerge as a widespread, routine monitoring tool in the near future due to its inherently high detection limits, cost, and inability to easily distinguish between viable and non-viable cells. Instead, metagenomics seems best poised for applications involving special circumstances otherwise challenging for culture-based and molecular (e.g., PCR-based) approaches such as the de novo detection of novel pathogens, cases of co-infection by more than one pathogen, and situations where it is important to assess the genomic composition of the pathogenic population(s) and/or its impact on the indigenous microbiome.

Gut microbiome and antibiotic resistance effects during travelers' diarrhea treatment and prevention

IMPORTANCE

The travelers' gut microbiome is potentially assaulted by acute and chronic perturbations (e.g., diarrhea, antibiotic use, and different environments). Prior studies of the impact of travel and travelers' diarrhea (TD) on the microbiome have not directly compared antibiotic regimens, and studies of different antibiotic regimens have not considered travelers' microbiomes. This gap is important to be addressed as the use of antibiotics to treat or prevent TD-even in moderate to severe cases or in regions with high infectious disease burden-is controversial based on the concerns for unintended consequences to the gut microbiome and antimicrobial resistance (AMR) emergence. Our study addresses this by evaluating the impact of defined antibiotic regimens (single-dose treatment or daily prophylaxis) on the gut microbiome and resistomes of deployed servicemembers, using samples collected during clinical trials. Our findings indicate that the antibiotic treatment regimens that were studied generally do not lead to adverse effects on the gut microbiome and resistome and identify the relative risks associated with prophylaxis. These results can be used to inform therapeutic guidelines for the prevention and treatment of TD and make progress toward using microbiome information in personalized medical care.

Persistent Salmonella infections in humans are associated with mutations in the BarA/SirA regulatory pathway

Several bacterial pathogens, including Salmonella enterica, can cause persistent infections in humans by mechanisms that are poorly understood. By comparing genomes of isolates longitudinally collected from 256 prolonged salmonellosis patients, we identified repeated mutations in global regulators, including the barA/sirA two-component regulatory system, across multiple patients and Salmonella serovars. Comparative RNA-seq analysis revealed that distinct mutations in barA/sirA led to diminished expression of Salmonella pathogenicity islands 1 and 4 genes, which are required for Salmonella invasion and enteritis. Moreover, barA/sirA mutants were attenuated in an acute salmonellosis mouse model and induced weaker transcription of host immune responses. In contrast, in a persistent infection mouse model, these mutants exhibited long-term colonization and prolonged shedding. Taken together, these findings suggest that selection of mutations in global virulence regulators facilitates persistent Salmonella infection in humans, by attenuating Salmonella virulence and inducing a weaker host inflammatory response.

Fecal microbiota transplantation promotes reduction of antimicrobial resistance by strain replacement

Multidrug-resistant organism (MDRO) colonization is a fundamental challenge in antimicrobial resistance. Limited studies have shown that fecal microbiota transplantation (FMT) can reduce MDRO colonization, but its mechanisms are poorly understood. We conducted a randomized, controlled trial of FMT for MDRO decolonization in renal transplant recipients called PREMIX (NCT02922816). Eleven participants were enrolled and randomized 1:1 to FMT or an observation period followed by delayed FMT if stool cultures were MDRO positive at day 36. Participants who were MDRO positive after one FMT were treated with a second FMT. At last visit, eight of nine patients who completed all treatments were MDRO culture negative. FMT-treated participants had longer time to recurrent MDRO infection versus PREMIX-eligible controls who were not treated with FMT. Key taxa (Akkermansia muciniphila, Alistipes putredinis, Phocaeicola dorei, Phascolarctobacterium faecium, Alistipes species, Mesosutterella massiliensis, Barnesiella intestinihominis, and Faecalibacterium prausnitzii) from the single feces donor used in the study that engrafted in recipients and metabolites such as short-chain fatty acids and bile acids in FMT-responding participants uncovered leads for rational microbiome therapeutic and diagnostic development. Metagenomic analyses revealed a previously unobserved mechanism of MDRO eradication by conspecific strain competition in an FMT-treated subset. Susceptible Enterobacterales strains that replaced baseline extended-spectrum β-lactamase-producing strains were not detectable in donor microbiota manufactured as FMT doses but in one case were detectable in the recipient before FMT. These data suggest that FMT may provide a path to exploit strain competition to reduce MDRO colonization.

cgMSI: pathogen detection within species from nanopore metagenomic sequencing data

BACKGROUND

Metagenomic sequencing is an unbiased approach that can potentially detect all the known and unidentified strains in pathogen detection. Recently, nanopore sequencing has been emerging as a highly potential tool for rapid pathogen detection due to its fast turnaround time. However, identifying pathogen within species is nontrivial for nanopore sequencing data due to the high sequencing error rate.

RESULTS

We developed the core gene alleles metagenome strain identification (cgMSI) tool, which uses a two-stage maximum a posteriori probability estimation method to detect pathogens at strain level from nanopore metagenomic sequencing data at low computational cost. The cgMSI tool can accurately identify strains and estimate relative abundance at 1× coverage.

CONCLUSIONS

We developed cgMSI for nanopore metagenomic pathogen detection within species. cgMSI is available at https://github.com/ZHU-XU-xmu/cgMSI .

Gut microbiome perturbation, antibiotic resistance, and Escherichia coli strain dynamics associated with international travel: a metagenomic analysis

BACKGROUND

Culture-based studies have shown that acquisition of extended-spectrum β-lactamase-producing Enterobacterales is common during international travel; however, little is known about the role of the gut microbiome before and during travel, nor about acquisition of other antimicrobial-resistant organisms. We aimed to identify (1) whether the gut microbiome provided colonisation resistance against antimicrobial-resistant organism acquisition, (2) the effect of travel and travel behaviours on the gut microbiome, and (3) the scale and global heterogeneity of antimicrobial-resistant organism acquisition.

METHODS

In this metagenomic analysis, participants were recruited at three US travel clinics (Boston, MA; New York, NY; and Salt Lake City, UT) before international travel. Participants had to travel internationally between Dec 8, 2017, and April 30, 2019, and have DNA extractions for stool samples both before and after travel for inclusion. Participants were excluded if they had at least one low coverage sample (<1 million read pairs). Stool samples were collected at home before and after travel, sent to a clinical microbiology laboratory to be screened for three target antimicrobial-resistant organisms (extended-spectrum β-lactamase-producing Enterobacterales, carbapenem-resistant Enterobacterales, and mcr-mediated colistin-resistant Enterobacterales), and underwent DNA extraction and shotgun metagenomic sequencing. We profiled metagenomes for taxonomic composition, antibiotic-resistant gene content, and characterised the Escherichia coli population at the strain level. We analysed pre-travel samples to identify the gut microbiome risk factors associated with acquisition of the three targeted antimicrobial resistant organisms. Pre-travel and post-travel samples were compared to identify microbiome and resistome perturbation and E coli strain acquisition associated with travel.

FINDINGS

A total of 368 individuals travelled between the required dates, and 296 had DNA extractions available for both before and after travel. 29 travellers were excluded as they had at least one low coverage sample, leaving a final group of 267 participants. We observed a perturbation of the gut microbiota, characterised by a significant depletion of microbial diversity and enrichment of the Enterobacteriaceae family. Metagenomic strain tracking confirmed that 67% of travellers acquired new strains of E coli during travel that were phylogenetically distinct from their pre-travel strains. We observed widespread enrichment of antibiotic-resistant genes in the gut, with a median 15% (95% CI 10-20, p<1 × 10-10) increase in burden (reads per kilobase per million reads). This increase included antibiotic-resistant genes previously classified as threats to public health, which were 56% (95% CI 36-91, p=2 × 10-11) higher in abundance after travel than before. Fluoroquinolone antibiotic-resistant genes were aquired by 97 (54%) of 181 travellers with no detected pre-travel carriage. Although we found that visiting friends or relatives, travel to south Asia, and eating uncooked vegetables were risk factors for acquisition of the three targeted antimicrobial resistant organisms, we did not observe an association between the pre-travel microbiome structure and travel-related antimicrobial-resistant organism acquisition.

INTERPRETATION

This work highlights a scale of E coli and antimicrobial-resistant organism acquisition by US travellers not apparent from previous culture-based studies, and suggests that strategies to control antimicrobial-resistant organisms addressing international traveller behaviour, rather than modulating the gut microbiome, could be worthwhile.

FUNDING

US Centers for Disease Control and Prevention and National Institute of Allergy and Infectious Diseases.

High-resolution strain-level microbiome composition analysis from short reads

BACKGROUND

Bacterial strains under the same species can exhibit different biological properties, making strain-level composition analysis an important step in understanding the dynamics of microbial communities. Metagenomic sequencing has become the major means for probing the microbial composition in host-associated or environmental samples. Although there are a plethora of composition analysis tools, they are not optimized to address the challenges in strain-level analysis: highly similar strain genomes and the presence of multiple strains under one species in a sample. Thus, this work aims to provide a high-resolution and more accurate strain-level analysis tool for short reads.

RESULTS

In this work, we present a new strain-level composition analysis tool named StrainScan that employs a novel tree-based k-mers indexing structure to strike a balance between the strain identification accuracy and the computational complexity. We tested StrainScan extensively on a large number of simulated and real sequencing data and benchmarked StrainScan with popular strain-level analysis tools including Krakenuniq, StrainSeeker, Pathoscope2, Sigma, StrainGE, and StrainEst. The results show that StrainScan has higher accuracy and resolution than the state-of-the-art tools on strain-level composition analysis. It improves the F1 score by 20% in identifying multiple strains at the strain level.

CONCLUSIONS

By using a novel k-mer indexing structure, StrainScan is able to provide strain-level analysis with higher resolution than existing tools, enabling it to return more informative strain composition analysis in one sample or across multiple samples. StrainScan takes short reads and a set of reference strains as input and its source codes are freely available at https://github.com/liaoherui/StrainScan . Video Abstract.

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.

Development of early life gut resistome and mobilome across gestational ages and microbiota-modifying treatments

BACKGROUND

Gestational age (GA) and associated level of gastrointestinal tract maturation are major factors driving the initial gut microbiota composition in preterm infants. Besides, compared to term infants, premature infants often receive antibiotics to treat infections and probiotics to restore optimal gut microbiota. How GA, antibiotics, and probiotics modulate the microbiota's core characteristics, gut resistome and mobilome, remains nascent.

METHODS

We analysed metagenomic data from a longitudinal observational study in six Norwegian neonatal intensive care units to describe the bacterial microbiota of infants of varying GA and receiving different treatments. The cohort consisted of probiotic-supplemented and antibiotic-exposed extremely preterm infants (n = 29), antibiotic-exposed very preterm (n = 25), antibiotic-unexposed very preterm (n = 8), and antibiotic-unexposed full-term (n = 10) infants. The stool samples were collected on days of life 7, 28, 120, and 365, and DNA extraction was followed by shotgun metagenome sequencing and bioinformatical analysis.

FINDINGS

The top predictors of microbiota maturation were hospitalisation length and GA. Probiotic administration rendered the gut microbiota and resistome of extremely preterm infants more alike to term infants on day 7 and ameliorated GA-driven loss of microbiota interconnectivity and stability. GA, hospitalisation, and both microbiota-modifying treatments (antibiotics and probiotics) contributed to an elevated carriage of mobile genetic elements in preterm infants compared to term controls. Finally, Escherichia coli was associated with the highest number of antibiotic-resistance genes, followed by Klebsiella pneumoniae and Klebsiella aerogenes.

INTERPRETATION

Prolonged hospitalisation, antibiotics, and probiotic intervention contribute to dynamic alterations in resistome and mobilome, gut microbiota characteristics relevant to infection risk.

FUNDING

Odd-Berg Group, Northern Norway Regional Health Authority.

Comprehensive insights from composition to functional microbe-based biodiversity of the infant human gut microbiota

During infancy, gut microbiota development is a crucial process involved in the establishment of microbe-host interactions which may persist throughout adulthood, and which are believed to influence host health. To fully understand the complexities of such interactions, it is essential to assess gut microbiota diversity of newborns and its associated microbial dynamics and relationships pertaining to health and disease. To explore microbial biodiversity during the first 3 years of human life, 10,935 shotgun metagenomic datasets were taxonomically and functionally classified. Microbial species distribution between infants revealed the presence of eight major Infant Community State Types (ICSTs), being dominated by 17 bacterial taxa, whose distribution was shown to correspond to the geographical origin and infant health status. In total, 2390 chromosomal sequences of the predominant taxa were reconstructed from metagenomic data and used in combination with 44,987 publicly available genomes to trace the distribution of microbial Population Subspecies (PS) within the different infant groups, revealing patterns of multistrain coexistence among ICSTs. Finally, implementation of a metagenomic- and metatranscriptomic-based metabolic profiling highlighted different enzymatic expression patterns of the gut microbiota that allowed us to acquire insights into mechanistic aspects of health-gut microbiota interplay in newborns. Comparison between metagenomic and metatranscriptomic data highlights how a complex environment like the human gut must be investigated by employing both sequencing methodologies and possibly supplemented with metabolomics approaches. While metagenomic analyses are very useful for microbial classification aimed at unveiling key players driving microbiota balances, using these data to explain functionalities of the microbiota is not always warranted.

Evolutionary investigations of the biosynthetic diversity in the skin microbiome using lsaBGC

Bacterial secondary metabolites, synthesized by enzymes encoded in biosynthetic gene clusters (BGCs), can underlie microbiome homeostasis and serve as commercialized products, which have historically been mined from a select group of taxa. While evolutionary approaches have proven beneficial for prioritizing BGCs for experimental characterization efforts to uncover new natural products, dedicated bioinformatics tools designed for comparative and evolutionary analysis of BGCs within focal taxa are limited. We thus developed l ineage s pecific a nalysis of BGCs (lsa BGC; https://github.com/Kalan-Lab/lsaBGC ) to aid exploration of microdiversity and evolutionary trends across homologous groupings of BGCs, gene cluster families (GCFs), in any bacterial taxa of interest. lsa BGC enables rapid and direct identification of GCFs in genomes, calculates evolutionary statistics and conservation for BGC genes, and builds a framework to allow for base resolution mining of novel variants through metagenomic exploration. Through application of the suite to four genera commonly found in skin microbiomes, we uncover new insights into the evolution and diversity of their BGCs. We show that the BGC of the virulence-associated carotenoid staphyloxanthin in Staphylococcus aureus is ubiquitous across the genus Staphylococcus . While one GCF encoding the biosynthesis of staphyloxanthin showcases evidence for plasmid-mediated horizontal gene transfer (HGT) between species, another GCF appears to be transmitted vertically amongst a sub-clade of skin-associated Staphylococcus . Further, the latter GCF, which is well conserved in S. aureus , has been lost in most Staphylococcus epidermidis , which is the most common Staphylococcus species on human skin and is also regarded as a commensal. We also identify thousands of novel single-nucleotide variants (SNVs) within BGCs from the Corynebacterium tuberculostearicum sp. complex, a narrow, multi-species clade that features the most prevalent Corynebacterium in healthy skin microbiomes. Although novel SNVs were approximately 10 times as likely to correspond to synonymous changes when located in the top five percentile of conserved sites, lsa BGC identified SNVs that defied this trend and are predicted to underlie amino acid changes within functionally key enzymatic domains. Ultimately, beyond supporting evolutionary investigations of BGCs, lsa BGC also provides important functionalities to aid efforts for the discovery or directed modification of natural products.

Comparison of long- and short-read metagenomic assembly for low-abundance species and resistance genes

Recent technological and computational advances have made metagenomic assembly a viable approach to achieving high-resolution views of complex microbial communities. In previous benchmarking, short-read (SR) metagenomic assemblers had the highest accuracy, long-read (LR) assemblers generated the most contiguous sequences and hybrid (HY) assemblers balanced length and accuracy. However, no assessments have specifically compared the performance of these assemblers on low-abundance species, which include clinically relevant organisms in the gut. We generated semi-synthetic LR and SR datasets by spiking small and increasing amounts of Escherichia coli isolate reads into fecal metagenomes and, using different assemblers, examined E. coli contigs and the presence of antibiotic resistance genes (ARGs). For ARG assembly, although SR assemblers recovered more ARGs with high accuracy, even at low coverages, LR assemblies allowed for the placement of ARGs within longer, E. coli-specific contigs, thus pinpointing their taxonomic origin. HY assemblies identified resistance genes with high accuracy and had lower contiguity than LR assemblies. Each assembler type's strengths were maintained even when our isolate was spiked in with a competing strain, which fragmented and reduced the accuracy of all assemblies. For strain characterization and determining gene context, LR assembly is optimal, while for base-accurate gene identification, SR assemblers outperform other options. HY assembly offers contiguity and base accuracy, but requires generating data on multiple platforms, and may suffer high misassembly rates when strain diversity exists. Our results highlight the trade-offs associated with each approach for recovering low-abundance taxa, and that the optimal approach is goal-dependent.

Comparative Genomic and Metagenomic Investigations of the Corynebacterium tuberculostearicum Species Complex Reveals Potential Mechanisms Underlying Associations To Skin Health and Disease

Corynebacterium are a diverse genus and dominant member of the human skin microbiome. Recently, we reported that the most prevalent Corynebacterium species found on skin, including Corynebacterium tuberculostearicum and Corynebacterium kefirresidentii, comprise a narrow species complex despite the diversity of the genus. Here, we apply high-resolution phylogenomics and comparative genomics to describe the structure of the C. tuberculostearicum species complex and highlight genetic traits which are enriched or depleted in it relative to other Corynebacterium. Through metagenomic investigations, we also find that individual species within the complex can associate with specific body sites. Finally, we discover that one species from the complex, C. kefirresidentii, increases in relative abundance during atopic dermatitis flares, and show that most genomes of this species encode a colocalized set of putative virulence genes. IMPORTANCE Corynebacterium are commonly found bacteria on the human skin. In this study, we perform comparative genomics to gain insight into genetic traits which differentiate a phylogenetically related group of Corynebacterium, the Corynebacterium tuberculostearicum species complex, that includes the most prevalent species from the genus in skin microbiomes. After resolving the presence of distinct species within the complex, we applied metagenomic analysis to uncover biogeographic associations of individual species within the complex with specific body sites and discovered that one species, commonly found in the nares of individuals, increases in abundance across multiple body sites during atopic dermatitis flares.

Identification of a prototype human gut Bifidobacterium longum subsp. longum strain based on comparative and functional genomic approaches

Bifidobacteria are extensively exploited for the formulation of probiotic food supplements due to their claimed ability to exert health-beneficial effects upon their host. However, most commercialized probiotics are tested and selected for their safety features rather than for their effective abilities to interact with the host and/or other intestinal microbial players. In this study, we applied an ecological and phylogenomic-driven selection to identify novel B. longum subsp. longum strains with a presumed high fitness in the human gut. Such analyses allowed the identification of a prototype microorganism to investigate the genetic traits encompassed by the autochthonous bifidobacterial human gut communities. B. longum subsp. longum PRL2022 was selected due to its close genomic relationship with the calculated model representative of the adult human-gut associated B. longum subsp. longum taxon. The interactomic features of PRL2022 with the human host as well as with key representative intestinal microbial members were assayed using in vitro models, revealing how this bifidobacterial gut strain is able to establish extensive cross-talk with both the host and other microbial residents of the human intestine.

Unitig level assembly graph based metagenome-assembled genome refiner (UGMAGrefiner): A tool to increase completeness and resolution of metagenome-assembled genomes

De novo assembly of next generation metagenomic reads is widely used to provide taxonomic and functional information of genomes in a microbial community. As strains are functionally specific, recovery of strain-resolved genomes is important but still a challenge. Unitigs and assembly graphs are mid-products generated during the assembly of reads into contigs, and they provide higher resolution for sequences connection information. In this study, we propose a new approach UGMAGrefiner (a unitig level assembly graph-based metagenome-assembled Genome refiner), which uses the connection and coverage information from unitig level assembly graphs to recruit unbinned unitigs to MAGs, adjust binning result, and infer unitigs shared by multiple MAGs. In two simulated datasets (Simdata and CAMI data) and one real dataset (GD02), it outperforms two state-of-the-art assembly graph-based binning refine tools in the refinement of MAGs' quality by stably increasing the completeness of genomes. UGMAGrefiner can identify genome specific clusters of genomes with below 99% average nucleotide identity for homologous sequences. For MAGs mixed with 99% similarity genome clusters, it could distinguish 8 out of 9 genomes in Simdata and 8 out of 12 genomes in CAMI data. In GD02 data, it could identify 16 new unitig clusters representing genome specific regions of mixed genomes and 4 unitig clusters representing new genomes from total 135 MAGs for further functional analysis. UGMAGrefiner provides an efficient way to obtain more complete MAGs and study genome specific functions. It will be useful to improve taxonomic and functional information of genomes after de novo assembly.

Statistical and Computational Methods for Microbial Strain Analysis

Microbial strains are interpreted as a lineage derived from a recent ancestor that have not experienced "too many" recombination events and can be successfully retrieved with culture-independent techniques using metagenomic sequencing. Such a strain variability has been increasingly shown to display additional phenotypic heterogeneities that affect host health, such as virulence, transmissibility, and antibiotics resistance. New statistical and computational methods have recently been developed to track the strains in samples based on shotgun metagenomics data either based on reference genome sequences or Metagenome-assembled genomes (MAGs). In this paper, we review some recent statistical methods for strain identifications based on frequency counts at a set of single nucleotide variants (SNVs) within a set of single-copy marker genes. These methods differ in terms of whether reference genome sequences are needed, how SNVs are called, what methods of deconvolution are used and whether the methods can be applied to multiple samples. We conclude our review with areas that require further research.

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.

Metagenomic Characterization of Multiple Genetically Modified Bacillus Contaminations in Commercial Microbial Fermentation Products

Genetically modified microorganisms (GMM) are frequently employed for manufacturing microbial fermentation products such as food enzymes or vitamins. Although the fermentation product is required to be pure, GMM contaminations have repeatedly been reported in numerous commercial microbial fermentation produce types, leading to several rapid alerts at the European level. The aim of this study was to investigate the added value of shotgun metagenomic high-throughput sequencing to confirm and extend the results of classical analysis methods for the genomic characterization of unauthorized GMM. By combining short- and long-read metagenomic sequencing, two transgenic constructs were characterized, with insertions of alpha-amylase genes originating from B. amyloliquefaciens and B. licheniformis, respectively, and a transgenic construct with a protease gene insertion originating from B. velezensis, which were all present in all four investigated samples. Additionally, the samples were contaminated with up to three unculturable Bacillus strains, carrying genetic modifications that may hamper their ability to sporulate. Moreover, several samples contained viable Bacillus strains. Altogether these contaminations constitute a considerable load of antimicrobial resistance genes, that may represent a potential public health risk. In conclusion, our study showcases the added value of metagenomics to investigate the quality and safety of complex commercial microbial fermentation products.

Detection of Klebsiella pneumoniae human gut carriage: a comparison of culture, qPCR, and whole metagenomic sequencing methods

Klebsiella pneumoniae is an important opportunistic healthcare-associated pathogen and major contributor to the global spread of antimicrobial resistance. Gastrointestinal colonization with K. pneumoniae is a major predisposing risk factor for infection and forms an important hub for the dispersal of resistance. Current culture-based detection methods are time consuming, give limited intra-sample abundance and strain diversity information, and have uncertain sensitivity. Here we investigated the presence and abundance of K. pneumoniae at the species and strain level within fecal samples from 103 community-based adults by qPCR and whole metagenomic sequencing (WMS) compared to culture-based detection. qPCR demonstrated the highest sensitivity, detecting K. pneumoniae in 61.2% and 75.8% of direct-fecal and culture-enriched sweep samples, respectively, including 52/52 culture-positive samples. WMS displayed lower sensitivity, detecting K. pneumoniae in 71.2% of culture-positive fecal samples at a 0.01% abundance cutoff, and was inclined to false positives in proportion to the relative abundance of other Enterobacterales present. qPCR accurately quantified K. pneumoniae to 16 genome copies/reaction while WMS could estimate relative abundance to at least 0.01%. Quantification by both methods correlated strongly with each other (Spearman's rho = 0.91). WMS also supported accurate intra-sample K. pneumoniae sequence type (ST)-level diversity detection from fecal microbiomes to 0.1% relative abundance, agreeing with the culture-based detected ST in 16/19 samples. Our results show that qPCR and WMS are sensitive and reliable tools for detection, quantification, and strain analysis of K. pneumoniae from fecal samples with potential to support infection control and enhance insights in K. pneumoniae gastrointestinal ecology.

Longitudinal multi-omics analyses link gut microbiome dysbiosis with recurrent urinary tract infections in women

Recurrent urinary tract infections (rUTIs) are a major health burden worldwide, with history of infection being a significant risk factor. While the gut is a known reservoir for uropathogenic bacteria, the role of the microbiota in rUTI remains unclear. We conducted a year-long study of women with (n = 15) and without (n = 16) history of rUTI, from whom we collected urine, blood and monthly faecal samples for metagenomic and transcriptomic interrogation. During the study 24 UTIs were reported, with additional samples collected during and after infection. The gut microbiome of individuals with a history of rUTI was significantly depleted in microbial richness and butyrate-producing bacteria compared with controls, reminiscent of other inflammatory conditions. However, Escherichia coli gut and bladder populations were comparable between cohorts in both relative abundance and phylogroup. Transcriptional analysis of peripheral blood mononuclear cells revealed expression profiles indicative of differential systemic immunity between cohorts. Altogether, these results suggest that rUTI susceptibility is in part mediated through the gut-bladder axis, comprising gut dysbiosis and differential immune response to bacterial bladder colonization, manifesting in symptoms.