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Bengtsson-Palme, J.

Publications and source records attributed to Bengtsson-Palme, J..

18 recordsLinked to original sources

The elusive resistome: a global comparison reveals large discrepancies among detection pipelines

Identifying antibiotic resistance genes (ARGs) from metagenomic data is critical for studying antimicrobial resistance across microbial communities and pathogens. However, there is no standardized methodology for ARG annotation. Here, we compare ten commonly used ARG detection pipelines by analysing over 270 million prokaryotic genes from the Global Microbial Gene Catalogue across 13 distinct habitats. We observed up to a 45-fold difference in the number of reported ARGs, with a mean Jaccard index of only 16% between pipelines. Pipeline selection profoundly impacted downstream biological interpretations, with drastic changes to estimates of ARG relative abundance and richness, to the characterization of pan- and core-resistomes, and to the class-level composition of the inferred resistome. ARG detection pipelines make different, defensible trade-offs, and no single approach should be treated as authoritative. Therefore, users should justify and communicate choices carefully, as our analyses show that, taken uncritically, the same data can support conflicting biological and ecological interpretations.

bioinformatics↗

Introducing a gastric microbial model community

Persistent colonization by Helicobacter pylori in the stomach is connected to the development of different gastric pathologies including gastric cancer. Around half of the worlds population is estimated to be colonized by H. pylori, but few develop symptoms. The bacterium dominates the gastric mucosa of individuals who are H. pylori-positive by conventional testing, however, low abundances of H. pylori have also been detected in individuals who test negative, suggesting low-level colonization The factors driving the predominance of H. pylori within the gastric microbiota remain unclear, as are its interactions with the gastric microbiota. Yet these interactions may offer important insights into the organisms colonization success and its role in disease. In this study, we developed a gastric microbial model community, consisting of five species with high abundance and prevalence in gastric samples based on transcriptional data: H. pylori, Escherichia coli, Pseudomonas aeruginosa, Streptococcus salivarius, and Lactobacillus kalixensis. We established growth parameters and methods to track species abundance in vitro. Our results show that H. pylori growth is partly inhibited in pair-wise cultures with all other community members, except with L. kalixensis. This inhibition can to a certain extent be explained by resource competition, pH modulation of the medium, and the initial inoculum ratio of the members. The gastric microbial model community will allow dissection of the genetic mechanisms behind H. pylori interactions with other members of the gastric microbiota, and how these interactions influence H. pylori pathogenesis, providing a non-invasive, low resource model for future studies of the gastric microbiome.

microbiology↗

Microbial community dynamics in a traditional Swiss mountain cheese over 142 years of cheesemaking

The history of cheesemaking is deeply intertwined with the evolution of microbial communities, from spontaneous fermentation to modern, standardized practices. Despite centuries of refinement, the most profound shifts in cheese production occurred in the last century, driven by advances in microbiology and production technologies. These changes have shaped the bacterial and viral communities within cheese, yet the specific impacts remain underexplored. Using shotgun metagenomics and 16S rRNA gene amplicon sequencing approaches, we examined microbial community changes in Raclette du Valais, a traditional Swiss cheese, using preserved cheese wheels from 1875 to 2017 from the same alpine dairy in Switzerland. Our results reveal that significant shifts in microbial community composition coincide with changes in production practices. Notably, the oldest cheese harbored a distinct bacterial community, dominated by Lactiplantibacillus paraplantarum, Streptococcus thermophilus, Pseudolactococcus laudensis, and taxa commonly associated with the gut environment, indicative of spontaneous fermentation and the use of calf stomach for milk coagulation. Functionally, we can also track the rise and fall of antibiotic resistance genes mirroring their use. Furthermore, we found that domestication of lactic acid bacteria predates the studied period, and that bacteriophage genera detected in 1875 are representatives of those commonly found in modern cheesemaking. These findings highlight how microbial communities have adapted to changing production methods and how human intervention, through practices like antibiotic use in animal husbandry, has influenced these ecosystems in remote alpine cheesemaking. Significance StatementCheesemaking relies on complex microbial ecosystems shaped by long-standing human practices, yet how these communities responded to the modernization of food production has remained largely unknown. By analyzing DNA preserved in historical cheese wheels from a single alpine dairy, we examine microbial community changes across a key technological transition. We show that modernization impacted bacterial composition and functional potential, that cheese microbiomes record the rise of agricultural antibiotic use, and that major cheese-associated phages and domesticated starter bacteria were already established over a century ago. These findings demonstrate that historical cheeses preserve long-term microbial records and offer a glimpse how changes in food production practices shape fermented-food microbiomes.

microbiology↗

Environmental reservoir of resistance genes for the last resort antibiotic Cefiderocol.

Antibiotic resistance poses a global public health threat. Cefiderocol, a recently introduced siderophore cephalosporin, employs a "Trojan Horse" mechanism by exploiting bacterial iron uptake systems for cell entry. Yet, resistant clinical isolates are already observed in clinics and resistance mechanisms are difficult to characterize. Here, we applied functional metagenomics to identify cefiderocol resistance genes. Functional metagenomic DNA libraries from diverse environmental samples collected across several countries were expressed in a cefiderocol-sensitive Escherichia coli host. This yielded four resistant clones with DNA originating from wastewater or freshwater DNA libraries. The identified antibiotic resistance genes (ARGs) causing an increase in cefiderocol minimum inhibitory concentrations encoded for beta-lactamases (VEB-3, OXA-372 homolog and YbxI homolog) and a partial penicillin binding protein homolog. Three of four shared closest homologs in pathogenic bacteria. One ARG was associated with a mobile genetic element and was broadly distributed across all wastewater samples from every country surveyed. This study underscores the critical importance of environmental surveillance for ARGs, particularly for novel agents like cefiderocol with limited understanding of resistance mechanisms.

microbiology↗

Community-promoted antibiotic resistance genes show increased dissemination among pathogens

Antibiotic resistance is increasing among bacterial pathogens, posing one of the most severe threats to future public health. A major contributor to the increasing resistance is the dissemination of mobile antibiotic resistance genes (ARGs) among bacterial communities. These genes are ubiquitously present in various environments and are especially diverse in the human gut and wastewater. Despite this, the clinical implications of the prevalence of ARGs in these bacterial communities remain unclear. In this study, we aimed to investigate how the prevalence of ARGs in human gut and wastewater microbiomes reflects their dissemination among important bacterial pathogens. To do this, we estimated the prevalence of >30,000 ARGs, including both well-known (established) and computationally predicted (latent) genes, in >6,000 metagenomic samples. From their prevalence in the human gut and wastewater, we identified four categories of ARGs: co-promoted, human gut (HG)-promoted, wastewater (WW)- promoted, and non-promoted. Our results showed that co-promoted ARGs were by far the most promiscuous, being more frequently found across multiple bacterial phyla, and more often co-localized with broad host range conjugative elements. Co-promoted ARGs were also found to be overrepresented among genes identified in multiple pathogenic species and exhibited an overall higher genetic compatibility with both pathogens and other typical residents of the human gut and wastewater microbiomes. Taken together, our results highlight the link between the promotion of ARGs in the human gut and wastewater microbiomes and their presence in human pathogens, and, thereby, the genes potential risk to human health.

bioinformatics↗

Seal milk oligosaccharides rival human milk complexity and exhibit functional dynamics during lactation

Breast milk oligosaccharides are crucial for neonatal development and health. Yet most milk research focuses on humans, or domesticated mammals that are historically poor in milk oligosaccharide complexity. Here, we perform an exhaustive mass spectrometry-driven structural characterization of milk oligosaccharides in a wild mammal, Atlantic grey seals (Halichoerus grypus), throughout their lactation period. Characterizing and quantifying 332 milk oligosaccharides, including 166 novel structures, we reveal seals to rival human milk in complexity, with seal free oligosaccharides reaching unprecedented 28 monosaccharides in size. Glycomics and metabolomics time course analysis establishes a concerted regulatory process reshaping the seal milk glycome throughout lactation,similar as in human milk. Functional analysis of herein newly characterized structures reveals anti-biofilm effects and immunomodulatory functions of seal milk oligosaccharides. We envision these findings to overturn long-held assumptions about milk complexity of non-human mammals and enable insights into the functional relevance of complex carbohydrates in breast milk.

biochemistry↗

Fish are poor sentinels for surveillance of riverine AMR

Effective surveillance of antimicrobial resistance (AMR) in the environment is crucial for assessing the human and animal health risk of AMR pollution. Wastewater treatment plants (WWTPs) are one of the main sources of AMR pollutants discharged into water bodies. One important factor for assessing the risks associated with such pollution is the colonization potential of the resistant bacteria (ARB) and resistance genes (ARGs) from the environment into human or animal microbiomes upon exposure. This study explores whether fish can act as sentinels for surveillance of AMR pollution in general and specifically the human colonization potential of ARB in rivers impacted by WWTP effluents. Two riverine fish species, Brown trout, and European bullhead, were sampled up- and downstream a German WWTP. The two fish species were chosen due to their different lifestyles: Trout are mainly actively swimming in the water phase, while bullheads are sedentary and river sediment-associated. The bacterial microbiomes and resistomes of fish gills, skin, and feces were compared with those of the respective river water and sediment up- and downstream of the WWTP. Microbiomes of both fish mirrored the changes in river water and sediment downstream of the WWTP, with significant shifts in bacterial community composition, particularly an increase in Proteobacteria and Verrucomicrobia. However, increases in ARG abundances observed in water and sediment downstream of the WWTP were not reflected in any of the fish-associated resistomes. This indicates that while the fish microbiome is sensitive to environmental changes, resistomes of poikilothermic animals such as fish are less responsive to colonization by ARB originating from WWTPs and may not serve as effective sentinels for assessing AMR pollution and colonization risks in freshwater environments. This study highlights the complexity of using wildlife as indicators for environmental AMR pollution and suggests that other species are better suited for surveillance efforts. HighlightsO_LIWWTP effluent affected downstream river microbiome composition of water and sediment C_LIO_LIWWTP effluent significantly increased the level of six tested ARGs downstream C_LIO_LIChanges in environmental microbiome composition were mirrored in trout and bullhead C_LIO_LINo effect of the WWTP effluent on resistomes and individual ARG abundance in fishes C_LI

microbiology↗

Genetic Adaptation to Amoxicillin in Escherichia coli: The Limited Role of dinB and katE

Bacteria can quickly adapt to sub-lethal concentrations of antibiotics. Several stress and DNA repair genes contribute to this adaptation process. However, the pathways leading to adaptation by acquisition of de novo mutations remain poorly understood. This study explored the roles of DNA polymerase IV (dinB) and catalase HP2 (katE) in E. colis adaptation to amoxicillin. These genes are thought to play essential roles in beta-lactam resistance - dinB in increasing mutation rates and katE in managing oxidative stress. By comparing the adaptation rates, transcriptomic profiles, and genetic changes of wild-type and knockout strains, we aimed to clarify the contributions of these genes to beta-lactam resistance. While all strains exhibited similar adaptation rates and mutations in the frdD gene and ampC operon, several unique mutations were acquired in the {Delta}katE and {Delta}dinB strains. Overall, this study distinguishes the contributions of general stress-related genes on the one hand, and dinB, and katE on the other hand, in development of beta-lactam resistance.

microbiology↗

Fluoroquinolone-Specific Resistance Trajectories in E. coli and their Dependence on the SOS-Response

Fluoroquinolones are essential for treating bacterial infections in both human and veterinary medicine. This study investigates the mechanisms behind acquired resistance to fluoroquinolones with a specific focus on the SOS response - a critical cellular pathway activated by DNA damage. Utilizing an experimental evolution approach, we exposed Escherichia coli to four fluoroquinolones and monitored the adaptation process. A recA knock-out mutant deficient in the SOS response was used as biological control. The emergence of resistance was accompanied by numerous DNA mutations, consisting of some observed often and others that infrequently appeared. Our findings indicate that the development of resistance depends in varying degrees on the SOS response among the tested fluoroquinolones, with notable dissimilarities in clinical resistance development. Resistance developed slowest to ciprofloxacin, then levofloxacin, followed by enrofloxacin, and fastest to moxifloxacin. Genomic analysis revealed distinct mutation profiles in cultures exposed to the tested antimicrobials, emphasizing the unique adaptation strategies of bacteria. This research underscores the importance of recognizing the differences among fluoroquinolones in scientific research and clinical practice.

microbiology↗

Metagenomic assemblies tend to break around antibiotic resistance genes

BackgroundAssembly of metagenomic samples can provide essential information about the mobility potential and taxonomic origin of antibiotic resistance genes (ARGs), and inform interventions to prevent further spread of resistant bacteria. However, ARGs typically occur in multiple genomic contexts across different species, representing a considerable challenge for the assembly process. Usually, this results in many fragmented contigs of unclear origin, complicating the risk assessment of ARG detections. To systematically investigate the impact of this issue on detection, quantification and contextualization of ARGs, we evaluated the performance of different assembly approaches, including genomic-, metagenomic- and transcriptomic-specialized assemblers. We quantified recovery and accuracy rates of each tool for ARGs both from in silico spiked metagenomic samples as well as real samples sequenced using both long- and short-read sequencing technologies. ResultsThe results revealed that none of the investigated tools can accurately capture genomic contexts present in samples of high complexity. The transcriptomic assembler Trinity showed a better performance in terms of reconstructing longer and fewer contigs matching unique genomic contexts, which can be beneficial for deciphering the taxonomic origin of ARGs. The currently commonly used metagenomic assembly tools metaSPAdes and MEGAHIT were able to identify the ARG repertoire but failed to fully recover the diversity of genomic contexts present in a sample. On top of that, in a complex scenario MEGAHIT produced very short contigs, which can lead to considerable underestimation of the resistome in a given sample. ConclusionsOur study shows that metaSPAdes and Trinity would be the preferable tools in terms of accuracy to recover correct genomic contexts around ARGs in metagenomic samples characterized by uneven coverages. Overall, the inability of assemblers to reconstruct long ARG-containing contigs has impacts on ARG quantification, suggesting that directly mapping reads to an ARG database might be necessary, at least as a complementary strategy, to get accurate ARG abundance and diversity measures.

bioinformatics↗

The global groundwater resistome: core ARGs and their dynamics - an in silico re-analysis of publicly available groundwater metagenomes

Despite the importance of groundwater as a drinking water resource, currently, no comprehensive picture regarding the global levels of antibiotic resistance genes (ARGs) in groundwater environments exists. Moreover, the biotic and abiotic factors that shape the groundwater resistome on the global scale remain to be explored. Herein, we attempted to fill this knowledge gap through in silico re-analysis of publicly available global groundwater metagenomes. First, nine ARGs encoding resistance to aminoglycosides (aadA, aph(3), and ant(3)), sulfonamides (sul1 and sul2), {beta}-lactams (blaOXA and blaTEM), tetracyclines (tet(C)) and macrolides (msr(E)) were identified to constitute the core groundwater resistome with high detection and abundance levels. Second, the global drivers of groundwater resistome composition were identified by applying a structural equation model with mixed effects to disentangle the individual contributions of each abiotic and biotic factor. Most notably, global effects of the origin of groundwater samples on the resistome were detected with samples from high-income countries (HICs) constantly displaying lower ARG and mobile genetic element (MGE) abundances than those from low-and-middle-income countries (LMICs). While these effects were consistent across antibiotic classes, biotic factors such as interactions of the groundwater microbiome with fungal or bacterial natural producers of antibiotics, or the co-occurrence of ARGs on mobile genetic elements (MGEs) played significant roles in shaping abundance patterns of resistance towards individual antibiotic classes. Only few ARGs correlated to individual bacterial genera, with microbial community composition in general weakly associated with resistome composition. In conclusion, we provide a first global picture of the resistome of low-anthropogenic impacted groundwater environments and the underlying anthropogenic and biotic drivers shaping it, which can be used as a baseline in future surveillance of antibiotic resistance.

microbiology↗

Meta-analysis reveals the global picture of antibiotic resistance gene prevalence across environments

The environment is an important component in the emergence and transmission of antimicrobial resistance (AMR). Despite that, little effort has been made to monitor AMR outside of clinical and veterinary settings. Partially, this is caused by a lack of comprehensive reference data for the vast majority of environments. To enable monitoring to detect deviations from the normal background resistance levels in the environment, it is necessary to establish a baseline of AMR in a variety of settings. In an attempt to establish this baseline level, we here performed a comprehensive literature survey, identifying 150 scientific papers containing relevant qPCR data on antimicrobial resistance genes (ARGs) in environments associated with potential routes for AMR dissemination. The collected data included 1594 samples distributed across 30 different countries and 12 sample types, in a time span from 2001 to 2020. We found that for most ARGs, the typically reported abundances in human impacted environments fell in an interval from 10-5 to 10-3 copies per 16S rRNA, roughly corresponding to one ARG copy in a thousand bacteria. Altogether these data represent a comprehensive overview of the occurrence and levels of ARGs in different environments, providing background data for risk assessment models within current and future AMR monitoring frameworks.

microbiology↗

What is the role of the environment in the emergence of novel antibiotic resistance genes? - A modelling approach

It is generally accepted that intervention strategies to curb antibiotic resistance cannot solely focus on human and veterinary medicine but must also consider environmental settings. While the environment clearly has a role in the transmission of resistant bacteria, it is less clear what role it plays in the emergence of novel types of resistance. It has been suggested that the environment constitutes an enormous recruitment ground for resistance genes to pathogens, but the extent to which this actually happens is unknown. In this study, we built a model framework for resistance emergence and used the available quantitative data on the relevant processes to identify the steps which are limiting the appearance of antibiotic resistance determinants in human or animal pathogens. We also assessed the effect of uncertainty in the available data on the model results. We found that in a majority of scenarios, the environment would only play a minor role in the emergence of novel resistance genes. However, the uncertainty around this role is enormous, highlighting an urgent need of more quantitative data to understand the role of the environment in antibiotic resistance development. Specifically, more data is most needed on the fitness costs of antibiotic resistance gene (ARG) carriage, the degree of dispersal of resistant bacteria from the environment to humans, but also the rates of mobilization and horizontal transfer of ARGs. Quantitative data on these processes is instrumental to determine which processes that should be targeted for interventions to curb development and transmission of resistance.

microbiology↗

The Organelle in the Room: Under-annotated Mitochondrial Reads Bias Coral Microbiome Analysis

The genomes of mitochondria and chloroplasts contain ribosomal RNA (rRNA) genes, reflecting their evolutionary ancestry as free-living bacteria prior to endosymbiosis. In microbiome studies of animals, plants, or other eukaryotic hosts, these organellar rRNAs are often amplified. If identified, they can be discarded, merely reducing sequencing depth. However, incorrectly annotated mitochondrial reads may compromise statistical analysis by distorting relative abundances of free-living microbes. We quantified this by reanalyzing 7,459 samples from seven 16S rRNA sequencing studies, including the microbiomes of 927 unique animal genera. We find that under-annotation of cryptic mitochondrial reads affects multiple of these large-scale cross-species microbiome comparisons, and can be severe in some samples. It also varies between host species, potentially biasing cross-species microbiome comparisons. We propose a straightforward solution: by supplementing existing taxonomies with diverse mitochondrial rRNA sequences, we resolve up to 97% of unique unclassified sequences in some entire studies as mitochondrial (14% averaged across all studies), without increasing false positive annotations in mitochondria-free mock communities. Overall, improved annotation decreases the proportion of unknown sequences by [≥]10-fold in 2,262 of 7,459 samples (30%), including representatives from 5 of 7 studies examined. While standard DADA2 analyses are severely affected, the default positive filter in Deblur run through QIIME2 discards many divergent mitochondrial sequences, preventing bias in analysis, but also making analysis of these sequences more difficult. We recommend leveraging mitochondrial sequence diversity to better identify, remove and analyze mitochondrial rRNA gene sequences in microbiome studies.

bioinformatics↗

Microbial retention and resistances in stormwater quality improvement devices treating road runoff

Current knowledge about the microbial communities that occur in in urban road runoff is scarce. Road runoff of trafficked roads can be heavily polluted and is treated by stormwater quality improvement devices (SQIDs). However, microbes may influence the treatment process of these devices or could lead to stress resistant opportunistic microbial strains. In this study, the microbial community in the influent, effluent and the filter materials for the removal of dissolved heavy metals of two different SQIDs were analyzed to determine the microbial load, retention, composition, and mobile resistance genes. Although the microbes were replaced by new taxa in the effluent, there was no major retention of microbial genera. Further, the bacterial abundance of the SQIDs effluent was relatively stable over time. The heavy metal content correlated with intl1 and with microbial genera. The filter media itself was enriched with Intl1 gene cassettes, carrying several heavy metal and multidrug resistance genes (e.g. czrA, czcA, silP, mexW and mexI), indicating that this is a hot spot for horizontal gene transfer. Overall, the results shed light on road runoff microbial communities, and pointed to distinct bacterial communities within the SQIDs, which subsequently influence the microbial community and the genes released with the treated water.

microbiology↗

Quantifying point-mutations in shotgun metagenomic data

Metagenomics has emerged as a central technique for studying the structure and function of microbial communities. Often the functional analysis is restricted to classification into broad functional categories. However, important phenotypic differences, such as resistance to antibiotics, are often the result of just one or a few point mutations in otherwise identical sequences. Bioinformatic methods for metagenomic analysis have generally been poor at accounting for this fact, resulting in a somewhat limited picture of important aspects of microbial communities. Here, we address this problem by providing a software tool called Mumame, which can distinguish between wildtype and mutated sequences in shotgun metagenomic data and quantify their relative abundances. We demonstrate the utility of the tool by quantifying antibiotic resistance mutations in several publicly available metagenomic data sets. We also identified that sequencing depth is a key factor to detect rare mutations. Therefore, much larger numbers of sequences may be required for reliable detection of mutations than for most other applications of shotgun metagenomics. Mumame is freely available from http://microbiology.se/software/mumame

bioinformatics↗

Introducing ribosomal tandem repeat barcoding for fungi

Sequence analysis of the various ribosomal genetic markers is the dominant molecular method for identification and description of fungi. However, there is little agreement on what ribosomal markers should be used, and research groups utilize different markers depending on what fungal groups are targeted. New environmental fungal lineages known only from DNA data reveal significant gaps in the coverage of the fungal kingdom both in terms of taxonomy and marker coverage in the reference sequence databases. In order to integrate references covering all of the ribosomal markers, we present three sets of general primers that allow the amplification of the complete ribosomal operon from the ribosomal tandem repeats. The primers cover all ribosomal markers (ETS, SSU, ITS1, 5.8S, ITS2, LSU, and IGS) from the 5 end of the ribosomal operon all the way to the 3 end. We coupled these primers successfully with third generation sequencing (PacBio and Nanopore sequencing) to showcase our approach on authentic fungal herbarium specimens. In particular, we were able to generate high-quality reference data with Nanopore sequencing in a high-throughput manner, showing that the generation of reference data can be achieved on a regular desktop computer without the need for a large-scale sequencing facility. The quality of the Nanopore generated sequences was 99.85 %, which is comparable with the 99.78 % accuracy described for Sanger sequencing. With this work, we hope to stimulate the generation of a new comprehensive standard of ribosomal reference data with the ultimate aim to close the huge gaps in our reference datasets.

genetics↗

Taxonomic identification from metagenomic and metabarcoding data using any genetic marker

Correct taxonomic identification of DNA sequences is central to studies of biodiversity using both shotgun metagenomic and metabarcoding approaches. However, there is no genetic marker that gives sufficient performance across all the biological kingdoms, hampering studies of taxonomic diversity in many groups of organisms. We here present a major update to Metaxa2 (http://microbiology.se/software/metaxa2/) that enables the use of any genetic marker for taxonomic classification of metagenome and amplicon sequence data.

bioinformatics↗