Publications by authors named "Fredrik Boulund"

26 Publications

  • Page 1 of 1

Novel strain of possesses traits important in gut adaptation and host-microbe interactions.

Gut Microbes 2022 Jan-Dec;14(1):2013761

Human Microbiome Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

Fecal microbiota transplantation (FMT) is an efficient treatment for recurrent infection and currently investigated as a treatment for other intestinal and systemic diseases. Better understanding of the species potentially transferred in FMT is needed. We isolated from a healthy fecal donor a novel strain E10-96H of , a recently described strictly anaerobic species currently represented only by the type strain. The whole genome sequence of E10-96H had over 98% similarity with the type strain. E10-96H carries 20 glycoside hydrolase encoding genes, degrades starch and thus may contribute to fiber degradation, cross-feeding of other species and butyrate production in the intestinal ecosystem. The strain carries pilus-like structures, harbors pilin genes in its genome and adheres to enterocytes but does not provoke a proinflammatory response. seems to have commensal behavior with the host epithelium, and its role in intestinal ecology should be studied further.
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http://dx.doi.org/10.1080/19490976.2021.2013761DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8726730PMC
December 2021

Multiomics and digital monitoring during lifestyle changes reveal independent dimensions of human biology and health.

Cell Syst 2021 Nov 30. Epub 2021 Nov 30.

Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki 00290, Finland; Science for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17165, Sweden. Electronic address:

We explored opportunities for personalized and predictive health care by collecting serial clinical measurements, health surveys, genomics, proteomics, autoantibodies, metabolomics, and gut microbiome data from 96 individuals who participated in a data-driven health coaching program over a 16-month period with continuous digital monitoring of activity and sleep. We generated a resource of >20,000 biological samples from this study and a compendium of >53 million primary data points for 558,032 distinct features. Multiomics factor analysis revealed distinct and independent molecular factors linked to obesity, diabetes, liver function, cardiovascular disease, inflammation, immunity, exercise, diet, and hormonal effects. For example, ethinyl estradiol, a common oral contraceptive, produced characteristic molecular and physiological effects, including increased levels of inflammation and impact on thyroid, cortisol levels, and pulse, that were distinct from other sources of variability observed in our study. In total, this work illustrates the value of combining deep molecular and digital monitoring of human health. A record of this paper's transparent peer review process is included in the supplemental information.
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http://dx.doi.org/10.1016/j.cels.2021.11.001DOI Listing
November 2021

Dysbiosis of the Human Oral Microbiome During the Menstrual Cycle and Vulnerability to the External Exposures of Smoking and Dietary Sugar.

Front Cell Infect Microbiol 2021 19;11:625229. Epub 2021 Mar 19.

Centre for Translational Microbiome Research, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.

Physiological hormonal fluctuations exert endogenous pressures on the structure and function of the human microbiome. As such, the menstrual cycle may selectively disrupt the homeostasis of the resident oral microbiome, thus compromising oral health. Hence, the aim of the present study was to structurally and functionally profile the salivary microbiome of 103 women in reproductive age with regular menstrual cycle, while evaluating the modifying influences of hormonal contraceptives, sex hormones, diet, and smoking. Whole saliva was sampled during the menstrual, follicular, and luteal phases (n = 309) of the cycle, and the participants reported questionnaire-based data concerning their life habits and oral or systemic health. No significant differences in alpha-diversity or phase-specific clustering of the overall microbiome were observed. Nevertheless, the salivary abundances of genera , , , and varied throughout the cycle, and a higher species-richness was observed during the luteal phase. While the overall community structure maintained relatively intact, its functional properties were drastically affected. In particular, 11 functional modules were differentially abundant throughout the menstrual cycle, including pentose phosphate metabolism, and biosynthesis of cobalamin and neurotransmitter gamma-aminobutyric acid. The menstrual cycle phase, but not oral contraceptive usage, was accountable for greater variations in the metabolic pathways of the salivary microbiome. Further co-risk factor analysis demonstrated that and were increased in current smokers, whereas high dietary sugar consumption modified the richness and diversity of the microbiome during the cycle. This is the first large study to systematically address dysbiotic variations of the oral microbiome during the course of menstrual cycle, and document the additive effect of smoking and sugar consumption as environmental risk factors. It reveals the structural resilience and functional adaptability of the oral microbiome to the endogenous hormonal pressures of the menstrual cycle, while revealing its vulnerability to the exogenous exposures of diet and smoking.
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http://dx.doi.org/10.3389/fcimb.2021.625229DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8018275PMC
July 2021

High Amounts of SARS-CoV-2 Precede Sickness Among Asymptomatic Health Care Workers.

J Infect Dis 2021 07;224(1):14-20

Karolinska University Hospital, Stockholm, Sweden.

Background: Whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity among asymptomatic subjects reflects past or future disease may be difficult to ascertain.

Methods: We tested 9449 employees at Karolinska University Hospital, Stockholm, Sweden for SARS-CoV-2 RNA and antibodies, linked the results to sick leave records, and determined associations with past or future sick leave using multinomial logistic regression.

Results: Subjects with high amounts of SARS-CoV-2 virus, indicated by polymerase chain reaction (PCR) cycle threshold (Ct) value, had the highest risk for sick leave in the 2 weeks after testing (odds ratio [OR], 11.97; 95% confidence interval [CI], 6.29-22.80) whereas subjects with low amounts of virus had the highest risk for sick leave in the 3 weeks before testing (OR, 6.31; 95% CI, 4.38-9.08). Only 2.5% of employees were SARS-CoV-2 positive while 10.5% were positive by serology and 1.2% were positive in both tests. Serology-positive subjects were not at excess risk for future sick leave (OR, 1.06; 95% CI, .71-1.57).

Conclusions: High amounts of SARS-CoV-2 virus, as determined using PCR Ct values, was associated with development of sickness in the next few weeks. Results support the concept that PCR Ct may be informative when testing for SARS-CoV-2. Clinical Trials Registration. NCT04411576.
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http://dx.doi.org/10.1093/infdis/jiab099DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7928785PMC
July 2021

Assessment of and Protocols for Sequence-Based Characterization of the Human Vaginal Microbiome.

mSphere 2020 11 18;5(6). Epub 2020 Nov 18.

Centre for Translational Microbiome Research, Department of Microbiology, Tumour and Cell Biology, Science for Life Laboratory, Karolinska Institutet, Solna, Sweden

The vaginal microbiome has been connected to a wide range of health outcomes. This has led to a thriving research environment but also to the use of conflicting methodologies to study its microbial composition. Here, we systematically assessed best practices for the sequencing-based characterization of the human vaginal microbiome. As far as 16S rRNA gene sequencing is concerned, the V1-V3 region performed best , but limitations of current sequencing technologies meant that the V3-V4 region performed equally well. Both approaches presented very good agreement with qPCR quantification of key taxa, provided that an appropriate bioinformatic pipeline was used. Shotgun metagenomic sequencing presents an interesting alternative to 16S rRNA gene amplification and sequencing but requires deeper sequencing and more bioinformatic expertise and infrastructure. We assessed different tools for the removal of host reads and the taxonomic annotation of metagenomic reads, including a new, easy-to-build and -use reference database of vaginal taxa. This curated database performed as well as the best-performing previously published strategies. Despite the many advantages of shotgun sequencing, none of the shotgun approaches assessed here agreed with the qPCR data as well as the 16S rRNA gene sequencing. The vaginal microbiome has been connected to various aspects of host health, including susceptibility to sexually transmitted infections as well as gynecological cancers and pregnancy outcomes. This has led to a thriving research environment but also to conflicting available methodologies, including many studies that do not report their molecular biological and bioinformatic methods in sufficient detail to be considered reproducible. This can lead to conflicting messages and delay progress from descriptive to intervention studies. By systematically assessing best practices for the characterization of the human vaginal microbiome, this study will enable past studies to be assessed more critically and assist future studies in the selection of appropriate methods for their specific research questions.
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http://dx.doi.org/10.1128/mSphere.00448-20DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677004PMC
November 2020

Integration of molecular profiles in a longitudinal wellness profiling cohort.

Nat Commun 2020 09 8;11(1):4487. Epub 2020 Sep 8.

Science for Life Laboratory, Department of Protein Science, KTH Royal Institute of Technology, Stockholm, Sweden.

An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies and immune cell profiling, complemented with gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine.
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http://dx.doi.org/10.1038/s41467-020-18148-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7479148PMC
September 2020

No evidence for a placental microbiome in human pregnancies at term.

Am J Obstet Gynecol 2021 03 29;224(3):296.e1-296.e23. Epub 2020 Aug 29.

Centre for Translational Microbiome Research, Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden; Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden. Electronic address:

Background: The placenta plays an important role in the modulation of pregnancy immunity; however, there is no consensus regarding the existence of a placental microbiome in healthy full-term pregnancies.

Objective: This study aimed to investigate the existence and origin of a placental microbiome.

Study Design: A cross-sectional study comparing samples (3 layers of placental tissue, amniotic fluid, vernix caseosa, and saliva, vaginal, and rectal samples) from 2 groups of full-term births: 50 women not in labor with elective cesarean deliveries and 26 with vaginal deliveries. The comparisons were performed using polymerase chain reaction amplification and DNA sequencing techniques and bacterial culture experiments.

Results: There were no significant differences regarding background characteristics between women who delivered by elective cesarean and those who delivered vaginally. Quantitative measurements of bacterial content in all 3 placental layers (quantitative polymerase chain reaction of the 16S ribosomal RNA gene) did not show any significant difference among any of the sample types and the negative controls. Here, 16S ribosomal RNA gene sequencing of the maternal side of the placenta could not differentiate between bacteria in the placental tissue and contamination of the laboratory reagents with bacterial DNA. Probe-specific quantitative polymerase chain reaction for bacterial taxa suspected to be present in the placenta could not detect any statistically significant difference between the 2 groups. In bacterial cultures, substantially more bacteria were observed in the placenta layers from vaginal deliveries than those from cesarean deliveries. In addition, 16S ribosomal RNA gene sequencing of bacterial colonies revealed that most of the bacteria that grew on the plates were genera typically found in human skin; moreover, it revealed that placentas delivered vaginally contained a high prevalence of common vaginal bacteria. Bacterial growth inhibition experiments indicated that placental tissue may facilitate the inhibition of bacterial growth.

Conclusion: We found no evidence to support the existence of a placental microbiome in our study of 76 term pregnancies, which used polymerase chain reaction amplification and sequencing techniques and bacterial culture experiments. Incidental findings of bacterial species could be due to contamination or to low-grade bacterial presence in some locations; such bacteria do not represent a placental microbiome per se.
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http://dx.doi.org/10.1016/j.ajog.2020.08.103DOI Listing
March 2021

Discovery of Species-unique Peptide Biomarkers of Bacterial Pathogens by Tandem Mass Spectrometry-based Proteotyping.

Mol Cell Proteomics 2020 03 15;19(3):518-528. Epub 2020 Jan 15.

Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy of the University of Gothenburg, SE-40234 Gothenburg, Sweden; Department of Clinical Microbiology, Sahlgrenska University Hospital, SE-413 46 Gothenburg, Region Västra Götaland, Sweden; Culture Collection University of Gothenburg (CCUG), Sahlgrenska Academy of the University of Gothenburg, SE-41346 Gothenburg, Sweden; Centre for Antibiotic Resistance Research (CARe), University of Gothenburg, SE-40234 Gothenburg, Sweden.

Mass spectrometry (MS) and proteomics offer comprehensive characterization and identification of microorganisms and discovery of protein biomarkers that are applicable for diagnostics of infectious diseases. The use of biomarkers for diagnostics is widely applied in the clinic and the use of peptide biomarkers is increasingly being investigated for applications in the clinical laboratory. Respiratory-tract infections are a predominant cause for medical treatment, although, clinical assessments and standard clinical laboratory protocols are time-consuming and often inadequate for reliable diagnoses. Novel methods, preferably applied directly to clinical samples, excluding cultivation steps, are needed to improve diagnostics of infectious diseases, provide adequate treatment and reduce the use of antibiotics and associated development of antibiotic resistance. This study applied nano-liquid chromatography (LC) coupled with tandem MS, with a bioinformatics pipeline and an in-house database of curated high-quality reference genome sequences to identify species-unique peptides as potential biomarkers for four bacterial pathogens commonly found in respiratory tract infections (RTIs): ; ; and The species-unique peptides were initially identified in pure cultures of bacterial reference strains, reflecting the genomic variation in the four species and, furthermore, in clinical respiratory tract samples, without prior cultivation, elucidating proteins expressed in clinical conditions of infection. For each of the four bacterial pathogens, the peptide biomarker candidates most predominantly found in clinical samples, are presented. Data are available via ProteomeXchange with identifier PXD014522. As proof-of-principle, the most promising species-unique peptides were applied in targeted tandem MS-analyses of clinical samples and their relevance for identifications of the pathogens, proteotyping, was validated, thus demonstrating their potential as peptide biomarker candidates for diagnostics of infectious diseases.
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http://dx.doi.org/10.1074/mcp.RA119.001667DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7050107PMC
March 2020

Effects of sampling strategy and DNA extraction on human skin microbiome investigations.

Sci Rep 2019 11 21;9(1):17287. Epub 2019 Nov 21.

Center for Translational Microbiome Research, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Science for Life Laboratory, Stockholm, Sweden.

The human skin is colonized by a wide array of microorganisms playing a role in skin disorders. Studying the skin microbiome provides unique obstacles such as low microbial biomass. The objective of this study was to establish methodology for skin microbiome analyses, focusing on sampling technique and DNA extraction. Skin swabs and scrapes were collected from 9 healthy adult subjects, and DNA extracted using 12 commercial kits. All 165 samples were sequenced using the 16S rRNA gene. Comparing the populations captured by eSwabs and scrapes, 99.3% of sequences overlapped. Using eSwabs yielded higher consistency. The success rate of library preparation applying different DNA extraction kits ranged from 39% to 100%. Some kits had higher Shannon alpha-diversity. Metagenomic shotgun analyses were performed on a subset of samples (N = 12). These data indicate that a reduction of human DNA from 90% to 57% is feasible without lowering the success of 16S rRNA library preparation and without introducing taxonomic bias. Using swabs is a reliable technique to investigate the skin microbiome. DNA extraction methodology is crucial for success of sequencing and adds a substantial amount of variation in microbiome analyses. Reduction of host DNA is recommended for interventional studies applying metagenomics.
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http://dx.doi.org/10.1038/s41598-019-53599-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6872721PMC
November 2019

The Prevotella copri Complex Comprises Four Distinct Clades Underrepresented in Westernized Populations.

Cell Host Microbe 2019 11 10;26(5):666-679.e7. Epub 2019 Oct 10.

CIBIO Department, University of Trento, 38123 Trento, Italy. Electronic address:

Prevotella copri is a common human gut microbe that has been both positively and negatively associated with host health. In a cross-continent meta-analysis exploiting >6,500 metagenomes, we obtained >1,000 genomes and explored the genetic and population structure of P. copri. P. copri encompasses four distinct clades (>10% inter-clade genetic divergence) that we propose constitute the P. copri complex, and all clades were confirmed by isolate sequencing. These clades are nearly ubiquitous and co-present in non-Westernized populations. Genomic analysis showed substantial functional diversity in the complex with notable differences in carbohydrate metabolism, suggesting that multi-generational dietary modifications may be driving reduced prevalence in Westernized populations. Analysis of ancient metagenomes highlighted patterns of P. copri presence consistent with modern non-Westernized populations and a clade delineation time pre-dating human migratory waves out of Africa. These findings reveal that P. copri exhibits a high diversity that is underrepresented in Western-lifestyle populations.
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http://dx.doi.org/10.1016/j.chom.2019.08.018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6854460PMC
November 2019

Identification and reconstruction of novel antibiotic resistance genes from metagenomes.

Microbiome 2019 04 1;7(1):52. Epub 2019 Apr 1.

Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden.

Background: Environmental and commensal bacteria maintain a diverse and largely unknown collection of antibiotic resistance genes (ARGs) that, over time, may be mobilized and transferred to pathogens. Metagenomics enables cultivation-independent characterization of bacterial communities but the resulting data is noisy and highly fragmented, severely hampering the identification of previously undescribed ARGs. We have therefore developed fARGene, a method for identification and reconstruction of ARGs directly from shotgun metagenomic data.

Results: fARGene uses optimized gene models and can therefore with high accuracy identify previously uncharacterized resistance genes, even if their sequence similarity to known ARGs is low. By performing the analysis directly on the metagenomic fragments, fARGene also circumvents the need for a high-quality assembly. To demonstrate the applicability of fARGene, we reconstructed β-lactamases from five billion metagenomic reads, resulting in 221 ARGs, of which 58 were previously not reported. Based on 38 ARGs reconstructed by fARGene, experimental verification showed that 81% provided a resistance phenotype in Escherichia coli. Compared to other methods for detecting ARGs in metagenomic data, fARGene has superior sensitivity and the ability to reconstruct previously unknown genes directly from the sequence reads.

Conclusions: We conclude that fARGene provides an efficient and reliable way to explore the unknown resistome in bacterial communities. The method is applicable to any type of ARGs and is freely available via GitHub under the MIT license.
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http://dx.doi.org/10.1186/s40168-019-0670-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444489PMC
April 2019

Proteotyping bacteria: Characterization, differentiation and identification of pneumococcus and other species within the Mitis Group of the genus Streptococcus by tandem mass spectrometry proteomics.

PLoS One 2018 10;13(12):e0208804. Epub 2018 Dec 10.

Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy of the University of Gothenburg, Gothenburg, Sweden.

A range of methodologies may be used for analyzing bacteria, depending on the purpose and the level of resolution needed. The capability for recognition of species distinctions within the complex spectrum of bacterial diversity is necessary for progress in microbiological research. In clinical settings, accurate, rapid and cost-effective methods are essential for early and efficient treatment of infections. Characterization and identification of microorganisms, using, bottom-up proteomics, or "proteotyping", relies on recognition of species-unique or associated peptides, by tandem mass spectrometry analyses, dependent upon an accurate and comprehensive foundation of genome sequence data, allowing for differentiation of species, at amino acid-level resolution. In this study, the high resolution and accuracy of MS/MS-based proteotyping was demonstrated, through analyses of the three phylogenetically and taxonomically most closely-related species of the Mitis Group of the genus Streptococcus: i.e., the pathogenic species, Streptococcus pneumoniae (pneumococcus), and the commensal species, Streptococcus pseudopneumoniae and Streptococcus mitis. To achieve high accuracy, a genome sequence database used for matching peptides was created and carefully curated. Here, MS-based, bottom-up proteotyping was observed and confirmed to attain the level of resolution necessary for differentiating and identifying the most-closely related bacterial species, as demonstrated by analyses of species of the Streptococcus Mitis Group, even when S. pneumoniae were mixed with S. pseudopneumoniae and S. mitis, by matching and identifying more than 200 unique peptides for each species.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0208804PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6287849PMC
May 2019

Computational discovery and functional validation of novel fluoroquinolone resistance genes in public metagenomic data sets.

BMC Genomics 2017 Sep 2;18(1):682. Epub 2017 Sep 2.

Department of Mathematical sciences, Chalmers university of Technology and University of Gothenburg, Gothenburg, Sweden.

Background: Fluoroquinolones are broad-spectrum antibiotics used to prevent and treat a wide range of bacterial infections. Plasmid-mediated qnr genes provide resistance to fluoroquinolones in many bacterial species and are increasingly encountered in clinical settings. Over the last decade, several families of qnr genes have been discovered and characterized, but their true prevalence and diversity still remain unclear. In particular, environmental and host-associated bacterial communities have been hypothesized to maintain a large and unknown collection of qnr genes that could be mobilized into pathogens.

Results: In this study we used computational methods to screen genomes and metagenomes for novel qnr genes. In contrast to previous studies, we analyzed an almost 20-fold larger dataset comprising almost 13 terabases of sequence data. In total, 362,843 potential qnr gene fragments were identified, from which 611 putative qnr genes were reconstructed. These gene sequences included all previously described plasmid-mediated qnr gene families. Fifty-two of the 611 identified qnr genes were reconstructed from metagenomes, and 20 of these were previously undescribed. All of the novel qnr genes were assembled from metagenomes associated with aquatic environments. Nine of the novel genes were selected for validation, and six of the tested genes conferred consistently decreased susceptibility to ciprofloxacin when expressed in Escherichia coli.

Conclusions: The results presented in this study provide additional evidence for the ubiquitous presence of qnr genes in environmental microbial communities, expand the number of known qnr gene variants and further elucidate the diversity of this class of resistance genes. This study also strengthens the hypothesis that environmental bacterial communities act as sources of previously uncharacterized qnr genes.
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http://dx.doi.org/10.1186/s12864-017-4064-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5581476PMC
September 2017

Typing and Characterization of Bacteria Using Bottom-up Tandem Mass Spectrometry Proteomics.

Mol Cell Proteomics 2017 06 18;16(6):1052-1063. Epub 2017 Apr 18.

From the ‡Division of Applied Mathematics and Statistics, Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-41296 Gothenburg, Sweden;

Methods for rapid and reliable microbial identification are essential in modern healthcare. The ability to detect and correctly identify pathogenic species and their resistance phenotype is necessary for accurate diagnosis and efficient treatment of infectious diseases. Bottom-up tandem mass spectrometry (MS) proteomics enables rapid characterization of large parts of the expressed genes of microorganisms. However, the generated data are highly fragmented, making downstream analyses complex. Here we present TCUP, a new computational method for typing and characterizing bacteria using proteomics data from bottom-up tandem MS. TCUP compares the generated protein sequence data to reference databases and automatically finds peptides suitable for characterization of taxonomic composition and identification of expressed antimicrobial resistance genes. TCUP was evaluated using several clinically relevant bacterial species (, , , and ), using both simulated data generated by peptide digestion and experimental proteomics data generated by liquid chromatography-tandem mass spectrometry (MS/MS). The results showed that TCUP performs correct peptide classifications at rates between 90.3 and 98.5% at the species level. The method was also able to estimate the relative abundances of individual species in mixed cultures. Furthermore, TCUP could identify expressed β-lactamases in an extended spectrum β-lactamase-producing (ESBL) strain, even when the strain was cultivated in the absence of antibiotics. Finally, TCUP is computationally efficient, easy to integrate in existing bioinformatics workflows, and freely available under an open source license for both Windows and Linux environments.
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http://dx.doi.org/10.1074/mcp.M116.061721DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5461537PMC
June 2017

Draft Genome Sequences of Six Strains of from Serotypes 5, 6A, 6B, 18C, 19A, and 23F.

Genome Announc 2017 Apr 6;5(14). Epub 2017 Apr 6.

Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

is a pathogenic bacterium found most commonly in the respiratory tract of humans and is a common cause of pneumonia and bacterial meningitis. Here, we report the draft genome sequences of six strains: CCUG 1350, CCUG 7206, CCUG 11780, CCUG 33774, CCUG 35180, and CCUG 35272.
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http://dx.doi.org/10.1128/genomeA.00125-17DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5383892PMC
April 2017

Draft Genome Sequence of Extended-Spectrum-β-Lactamase-Producing Escherichia coli Strain CCUG 62462, Isolated from a Urine Sample.

Genome Announc 2016 Dec 15;4(6). Epub 2016 Dec 15.

Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden.

The draft genome sequence has been determined for an extended-spectrum-β-lactamase (ESBL)-producing (bla) Escherichia coli strain (CCUG 62462), composed of 119 contigs and a total size of 5.27 Mb. This E. coli is serotype O25b and sequence type 131, a pandemic clonal group, causing worldwide antimicrobial-resistant infections.
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http://dx.doi.org/10.1128/genomeA.01382-16DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5159571PMC
December 2016

Strategies to improve usability and preserve accuracy in biological sequence databases.

Proteomics 2016 09;16(18):2454-60

Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.

Biology is increasingly dependent on large-scale analysis, such as proteomics, creating a requirement for efficient bioinformatics. Bioinformatic predictions of biological functions rely upon correctly annotated database sequences, and the presence of inaccurately annotated or otherwise poorly described sequences introduces noise and bias to biological analyses. Accurate annotations are, for example, pivotal for correct identification of polypeptide fragments. However, standards for how sequence databases are organized and presented are currently insufficient. Here, we propose five strategies to address fundamental issues in the annotation of sequence databases: (i) to clearly separate experimentally verified and unverified sequence entries; (ii) to enable a system for tracing the origins of annotations; (iii) to separate entries with high-quality, informative annotation from less useful ones; (iv) to integrate automated quality-control software whenever such tools exist; and (v) to facilitate postsubmission editing of annotations and metadata associated with sequences. We believe that implementation of these strategies, for example as requirements for publication of database papers, would enable biology to better take advantage of large-scale data.
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http://dx.doi.org/10.1002/pmic.201600034DOI Listing
September 2016

Draft Genome Sequence of Moraxella catarrhalis Type Strain CCUG 353T.

Genome Announc 2016 Jun 16;4(3). Epub 2016 Jun 16.

Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden Culture Collection University of Gothenburg (CCUG), Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

Moraxella catarrhalis is a Gram-negative commensal and pathogenic bacterium found in the human respiratory tract. It is associated with otitis media and respiratory tract infections. Here, we report the draft genome sequence of M. catarrhalis type strain CCUG 353(T), composed of 18 contigs and a total size of 1.89 Mb.
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http://dx.doi.org/10.1128/genomeA.00552-16DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4911475PMC
June 2016

Draft Genome Sequence of Streptococcus gordonii Type Strain CCUG 33482T.

Genome Announc 2016 Mar 24;4(2). Epub 2016 Mar 24.

Culture Collection University of Gothenburg (CCUG), Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

Streptococcus gordoniitype strain CCUG 33482(T)is a member of theStreptococcus mitisgroup, isolated from a case of subacute bacterial endocarditis. Here, we report the draft genome sequence ofS. gordoniiCCUG 33482(T), composed of 41 contigs of a total size of 2.15 Mb with 2,061 annotated coding sequences.
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http://dx.doi.org/10.1128/genomeA.00175-16DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4807240PMC
March 2016

Tentacle: distributed quantification of genes in metagenomes.

Gigascience 2015 7;4:40. Epub 2015 Sep 7.

Division of Statistics, Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.

Background: In metagenomics, microbial communities are sequenced at increasingly high resolution, generating datasets with billions of DNA fragments. Novel methods that can efficiently process the growing volumes of sequence data are necessary for the accurate analysis and interpretation of existing and upcoming metagenomes.

Findings: Here we present Tentacle, which is a novel framework that uses distributed computational resources for gene quantification in metagenomes. Tentacle is implemented using a dynamic master-worker approach in which DNA fragments are streamed via a network and processed in parallel on worker nodes. Tentacle is modular, extensible, and comes with support for six commonly used sequence aligners. It is easy to adapt Tentacle to different applications in metagenomics and easy to integrate into existing workflows.

Conclusions: Evaluations show that Tentacle scales very well with increasing computing resources. We illustrate the versatility of Tentacle on three different use cases. Tentacle is written for Linux in Python 2.7 and is published as open source under the GNU General Public License (v3). Documentation, tutorials, installation instructions, and the source code are freely available online at: http://bioinformatics.math.chalmers.se/tentacle.
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http://dx.doi.org/10.1186/s13742-015-0078-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4562114PMC
July 2016

Proteotyping: Proteomic characterization, classification and identification of microorganisms--A prospectus.

Syst Appl Microbiol 2015 Jun 11;38(4):246-57. Epub 2015 Apr 11.

Department of Clinical Microbiology, Sahlgrenska University Hospital, SE-41346 Gothenburg, Sweden; Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy of the University of Gothenburg, SE-40234 Gothenburg, Sweden; Culture Collection University of Gothenburg (CCUG), SE-41346 Gothenburg, Sweden.

Modern microbial systematics requires a range of methodologies for the comprehensive characterization, classification and identification of microorganisms. While whole-genome sequences provide the ultimate reference for defining microbial phylogeny and taxonomy, selected biomarker-based strategies continue to provide the means for the bulk of microbial systematic studies. Proteomics, the study of the expression of genes, as well as the structure and function of the resulting proteins, offers indirect measures of genome sequence data. Recent developments in applications of proteomics for analyzing microorganisms have paralleled the growing microbial genome sequence database, as well as the evolution of mass spectrometry (MS) instrumentation and bioinformatics. MALDI-TOF MS, which generates proteomic mass patterns for 'fingerprint'-based characterizations, has provided a marked breakthrough for microbial identification. However, MALDI-TOF MS is limited in the number of targets that can be detected for strain characterization. Advanced methods of tandem mass spectrometry, in which proteins and peptides generated from proteins, are characterized and identified, using LC-MS/MS, provide the ability to detect hundreds or thousands of expressed microbial strain markers for high-resolution characterizations and identifications. Model studies demonstrate the application of proteomics-based analyses for bacterial species- and strain-level detection and identification and for characterization of environmentally relevant, metabolically diverse bacteria. Proteomics-based approaches represent an emerging complement to traditional methods of characterizing microorganisms, enabling the elucidation of the expressed biomarkers of genome sequence information, which can be applied to 'proteotyping' applications of microorganisms at all taxonomic levels.
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http://dx.doi.org/10.1016/j.syapm.2015.03.006DOI Listing
June 2015

Shotgun metagenomics reveals a wide array of antibiotic resistance genes and mobile elements in a polluted lake in India.

Front Microbiol 2014 2;5:648. Epub 2014 Dec 2.

Department of Infectious Diseases, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg Gothenburg, Sweden.

There is increasing evidence for an environmental origin of many antibiotic resistance genes. Consequently, it is important to identify environments of particular risk for selecting and maintaining such resistance factors. In this study, we described the diversity of antibiotic resistance genes in an Indian lake subjected to industrial pollution with fluoroquinolone antibiotics. We also assessed the genetic context of the identified resistance genes, to try to predict their genetic transferability. The lake harbored a wide range of resistance genes (81 identified gene types) against essentially every major class of antibiotics, as well as genes responsible for mobilization of genetic material. Resistance genes were estimated to be 7000 times more abundant than in a Swedish lake included for comparison, where only eight resistance genes were found. The sul2 and qnrD genes were the most common resistance genes in the Indian lake. Twenty-six known and 21 putative novel plasmids were recovered in the Indian lake metagenome, which, together with the genes found, indicate a large potential for horizontal gene transfer through conjugation. Interestingly, the microbial community of the lake still included a wide range of taxa, suggesting that, across most phyla, bacteria has adapted relatively well to this highly polluted environment. Based on the wide range and high abundance of known resistance factors we have detected, it is plausible that yet unrecognized resistance genes are also present in the lake. Thus, we conclude that environments polluted with waste from antibiotic manufacturing could be important reservoirs for mobile antibiotic resistance genes.
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http://dx.doi.org/10.3389/fmicb.2014.00648DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4251439PMC
December 2014

In vitro assessment of platelet concentrates with multiple electrode aggregometry.

Platelets 2015 7;26(2):132-7. Epub 2014 Jul 7.

Department of Cardiothoracic Surgery, Sahlgrenska University Hospital , Gothenburg , Sweden .

Storage impairs platelet function. It was hypothesized that multiple electrode aggregometry in vitro could be used to follow aggregability in platelet concentrates over time and that the results predict the efficacy of platelet transfusion in an ex vivo transfusion model. In vitro platelet aggregability was assessed in apheresis and pooled buffy coat platelet concentrates (BCs) (n = 13 each) using multiple electrode aggregometry with different agonists 1, 3, 5 and 7 days after preparation. In the ex vivo transfusion model, whole blood samples from nine healthy volunteers were collected every second day. The samples were supplemented with stored platelets (+146 × 10(9) × l(-1)) from the same unit 1, 3, 5 and 7 days after preparation. Platelet aggregability was assessed in the concentrate and in the whole blood samples before and after platelet supplementation. There was a continuous reduction in in vitro platelet aggregability over time in both apheresis and pooled BCs. The same pattern was observed after ex vivo addition of apheresis and pooled BCs to whole blood samples. The best correlation between in vitro aggregability and changes in aggregation after addition was achieved with collagen as agonist (r = 0.67, p < 0.001). In conclusion, multiple electrode aggregometry can be used to follow aggregability in platelet concentrates in vitro, and the results predict with moderate accuracy changes in aggregation after addition of platelet concentrate to whole blood samples.
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http://dx.doi.org/10.3109/09537104.2014.898141DOI Listing
November 2015

Functional verification of computationally predicted qnr genes.

Ann Clin Microbiol Antimicrob 2013 Nov 21;12:34. Epub 2013 Nov 21.

Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden.

Background: The quinolone resistance (qnr) genes are widely distributed among bacteria. We recently developed and applied probabilistic models to identify tentative novel qnr genes in large public collections of DNA sequence data including fragmented metagenomes.

Findings: By using inducible recombinant expressions systems the functionality of four identified qnr candidates were evaluated in Escherichia coli. Expression of several known qnr genes as well as two novel candidates provided fluoroquinolone resistance that increased with elevated inducer concentrations. The two novel, functionally verified qnr genes are termed Vfuqnr and assembled qnr 1. Co-expression of two qnr genes suggested non-synergistic action.

Conclusion: The combination of a computational model and recombinant expression systems provides opportunities to explore and identify novel antibiotic resistance genes in both genomic and metagenomic datasets.
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http://dx.doi.org/10.1186/1476-0711-12-34DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4222258PMC
November 2013

A novel method to discover fluoroquinolone antibiotic resistance (qnr) genes in fragmented nucleotide sequences.

BMC Genomics 2012 Dec 11;13:695. Epub 2012 Dec 11.

Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Göteborg, SE-412 96, Sweden.

Background: Broad-spectrum fluoroquinolone antibiotics are central in modern health care and are used to treat and prevent a wide range of bacterial infections. The recently discovered qnr genes provide a mechanism of resistance with the potential to rapidly spread between bacteria using horizontal gene transfer. As for many antibiotic resistance genes present in pathogens today, qnr genes are hypothesized to originate from environmental bacteria. The vast amount of data generated by shotgun metagenomics can therefore be used to explore the diversity of qnr genes in more detail.

Results: In this paper we describe a new method to identify qnr genes in nucleotide sequence data. We show, using cross-validation, that the method has a high statistical power of correctly classifying sequences from novel classes of qnr genes, even for fragments as short as 100 nucleotides. Based on sequences from public repositories, the method was able to identify all previously reported plasmid-mediated qnr genes. In addition, several fragments from novel putative qnr genes were identified in metagenomes. The method was also able to annotate 39 chromosomal variants of which 11 have previously not been reported in literature.

Conclusions: The method described in this paper significantly improves the sensitivity and specificity of identification and annotation of qnr genes in nucleotide sequence data. The predicted novel putative qnr genes in the metagenomic data support the hypothesis of a large and uncharacterized diversity within this family of resistance genes in environmental bacterial communities. An implementation of the method is freely available at http://bioinformatics.math.chalmers.se/qnr/.
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http://dx.doi.org/10.1186/1471-2164-13-695DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3543242PMC
December 2012
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