Functional analysis of the pediatric multiple sclerosis microbiome
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Functional analysis of the pediatric multiple sclerosis microbiome Ali Mirza1, Feng Zhu1, Natalie Knox2, Jessica D Forbes2,3, Gary Van Domselaar2, Charles Bernstein4, Morag Graham2, Ruth Ann Marrie4, Janace Hart5, E. Ann Yeh3, Amit Bar-Or6, Julia O’Mahony3, William Hsiao1, Brenda Banwell6, Emmanuelle Waubant5, Helen Tremlett1 1University of British Columbia, School of Medicine, Vancouver, Canada, 2Public Health Agency of Canada, National Microbiology Laboratory, Winnipeg, Canada, 3University of Toronto, School of Medicine, Toronto, Canada, 4 University of Manitoba, School of Medicine, Winnipeg, Canada, 5University of California, San Francisco, School of Medicine, San Francisco, CA, 6University of Pennsylvania, School of Medicine, Philadelphia, PA Objective: Metagenomic sequencing reveals the functional potential of the Multiple Sclerosis (MS) gut microbiome. We examined the gut microbiome functional potential by metagenomic analysis of stool samples from pediatric MS cases and controls. Methods: Persons ≤21 years old enrolled in the Canadian Pediatric Demyelinating Disease Network who provided a stool sample were included for study. Twenty MS cases were matched to 20 non-affected controls by sex, age (± 3 years), stool consistency (Bristol Stool Scale, BSS) and, when possible, by race. Shotgun metagenomic reads were generated using the Illumina NextSeq platform and assembled using MEGAHIT. Metabolic pathway analysis was used to compare the gut microbiome between cases and controls, as well as cases by DMD status. Gene ontology classifications were used to assess α-diversity and differential abundance analyses (based on the negative binomial distribution). Results: The MS cases were aged 13.6 mean years at symptom onset. On average, MS cases and controls were 16.1 and 15.4 years old at the time of stool collection and 80% of each group were girls. Eight MS cases were DMD naïve. Richness of gene ontology classifications did not differ by disease status or DMD status (all p>0.4). However, differential analysis of metabolic pathways indicated that the relative abundance of tryptophan degradation (via the kynurenine pathway; LFC 13; 95%CI: 8–19; p
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Associations between Prenatal Vaginal Microbiota and Symptoms of Depression or Anxiety: Pregnancy and Postpartum
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Associations between Prenatal Vaginal Microbiota and Symptoms of Depression or Anxiety: Pregnancy and Postpartum Abstract Body: Introduction: Depression and anxiety affect between 13-20% of women in the prenatal and postpartum period. Depression and anxiety around and during pregnancy have negative sequalae on the mother, child, and family. Changes in the vaginal microbiome with stress during pregnancy have been observed previously, as one study found an association between chronic maternal stress and increased rates of bacterial vaginosis (BV), which increases the risk for preterm labor. Associations between chronic stress and having a major depressive episode have also been observed. The present study aims to elucidate associations between the prenatal vaginal microbiome and maternal mental health factors such as anxiety and depression in either the prenatal or postpartum period. Methods: Women were recruited during their first prenatal visit. Self-reported diagnoses of anxiety and depression, scores on the Edinburgh Postpartum Depression Scale (EPDS), and self-reported anti-depressant and anti-anxiolytic use were collected at three time points: the first prenatal visit (P1), in the third trimester (P2), and one month postpartum (PP). Vaginal swabs for microbiota analysis were collected in the third trimester (n= 40). The DNA from vaginal swabs was extracted, and PCR amplification was performed on the V4 region of the 16S rRNA gene. Sequence reads were processed in mothur. Alpha (Chao1, Shannon, Inverse Simpson) and beta diversity (Bray-Curtis, Sorensen) were calculated in R with the vegan package. The associations between the total EPDS and anxiety as assessed via question 4 on the EPDS (P1, PP), self-report of depression (P1, PP) and/or anxiety diagnoses (PP), anti-depressant and/or anti-anxiolytic medication (P1, P2, PP) and the vaginal bacterial alpha and beta diversity measures were tested using either Wilcoxon, Spearman, or PERMANOVA tests. Results: Women were between the ages of 19-40, most were college graduates, 76% were married. A higher score on the prenatal EPDS was associated with a less diverse and less even vaginal microbiota as well as lower levels of Bifidobacteriaceae in the vaginal community. The use of antidepressants in the third trimester of pregnancy was associated with lower diversity and evenness of the vaginal microbiota as well as lower levels of Bifidobacteriaceae in the vaginal community. Higher maternal anxiety in the prenatal period, as assessed via question 4 on the EPDS, was associated with less richness, evenness, and diversity of the vaginal microbiota. The community structure and composition of the vaginal microbiota differed based on level of scoring on the EPDS Anxiety question in the prenatal period with higher scores associated with lower levels of Lachnospiraceae, Bifidobacteriaceae, Prevotella, Bateroides, Sneathia, and higher levels of Lactobacillus in the vaginal microbiota. Conclusion: Maternal depression or anxiety during and around the pregnancy period are associated with differences in the vaginal microbiota. However, larger sample sizes will be needed to fully elucidate these relationships. Authors and Affiliations: Anfal Marafie1,2, Kameron Y. Sugino1, Nigel Paneth3,4, Rebecca Knickmeyer4,5, Kim McKee6, Sarah S. Comstock1 1Department of Food Science and Human Nutrition, Michigan State University, East Lansing, Michigan 2College of Human Medicine, Michigan State University, East Lansing, Michigan 3Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, Michigan. 4 Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, East Lansing, Michigan. 5Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan. 6 Department of Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan
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Infant antibiotic use alters the fungal mycobiome and induces Malassezia sp. overgrowth
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Infant antibiotic use alters the fungal mycobiome and induces Malassezia sp. overgrowth Erik van Tilburg Bernardes1,2, Stephen B Freedman1, Marie-Claire Arrieta1,2 1University of Calgary, Department of Pediatrics, Calgary, Canada. 2University of Calgary, Department of Physiology and Pharmacology, Calgary, Canada. Designed to treat bacterial infections, antibiotics also impact the microbiome. The characterization of antibiotic-induced microbiome alterations during early life is critical, as these can lead to immune and metabolic diseases. However, while the gut microbiome comprises a multi-kingdom community of microorganisms, little is known on the impact of antibiotics on non-bacterial microbes. Fungi are important members of the gut microbiome that have gained attention due to their role in host immune development. Yet, the direct implications of antibiotic use on the infant mycobiome, and how these may impact infant development are largely unexplored. We conducted an observational, prospective clinical study to investigate the impact of antibiotic use on the mycobiome of young infants (
Speaker(s):Maternal obesity impacts newborn microbiota Enterobacteriaceae produced LPS and reprograms bone marrow derived macrophages: a trained immunity phenotype in early life. Robins WP1, Soderborg TK2, Barbour LA2, Hernandez T2, Frank D2, Krebs NA2, Jonscher KA3, and Friedman JE2,3 1Dept. of Microbiology, Harvard Medical School, 2University of Colorado Anschutz Medical Campus, 3University of Oklahoma School of Medicine, Harold Hamm Diabetes Center. The neonatal fecal microbiota is normally dominated early with Enterobacteriaceae (EntB), a necessary primer for immune activation. The colonization of certain EntB strains in the newborn infant as founders may therefore have a profound influence on microbiota succession in early life and also the regulation and programming of the infant innate immune system. To begin to investigate how changes in EntB shapes the innate immune system, we collected stool from two distinct newborn infant cohorts, those from mothers with high >30 or normal
Speaker(s):Does early life translocation of commensal microbes shape humoral immunity? Jamal Green, Jean-Bernard Lubin PhD, Sarah Maddux, Tereza Duranova, Lidiya Denu, Matthew Sullivan, & Michael Silverman MD/PhD Children’s Hospital of Philadelphia, University of Pennsylvania In mice and humans, there is growing evidence that early-life microbial interactions impact long-term immune system function. Without microbial colonization during the first weeks of life, a normal immune system does not develop. Even if microbes are introduced during adulthood, immune components such as invariant natural killer T cells and allergic IgE responses do not return to physiological levels. Furthermore, if the microbiota is perturbed with antibiotics during early life, there is increased susceptibility to pathological inflammation, autoimmunity, or cancer later in life. The Silverman lab demonstrated that autoimmunity in the non-obese diabetic (NOD) murine model of diabetes is affected by the early life microbial environment as well (PNAS, 2017). These studies demonstrate that critical immunological interactions with microbiota occur in early life, yet the underlying mechanisms of peripheral immune education remain elusive. Further, the specific location for these key microbiota-immune system interactions have not been clearly defined. We hypothesize that translocation of live commensal bacteria from the intestines to the mesenteric lymph node during the early life period is a critical physiologic mechanism for the education of the immune system. To rigorously study the early-life microbiota, we developed a novel consortium of 9 culturable bacteria (PedsCom) that represent over 90% of the intestinal bacteria in pre-weaning NOD mice. In healthy mice and humans, systemic IgGs capable of binding a subset of commensals develop shortly after weaning, but little is known of how and why certain commensals induce these systemic commensal responses. Our preliminary data suggest that there is a limited window in early life, in which live commensal bacteria can be found in the mesenteric lymph nodes, and that these bacteria that translocate in early life induce systemic IgG responses that is specific for the same commensal bacteria. Studying the interplay between microbial translocation, humoral response to commensal bacteria, and colonization dynamics, will enhance our understanding of how early life microbes drive immune system development.
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Divergence of gut bacteria through the selection of genetic variations by milk exosomes
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Divergence of gut bacteria through the selection of genetic variations by milk exosomes Janos Zempleni,1 Fang Zhou,1 Haluk Dogan,2 Juan Cui2 University of Nebraska-Lincoln, Departments of 1Nutrition and Health Sciences and 2Computer Science and Engineering Background: Exosomes play an important role in cell-to-cell communication and are present in most body fluids including milk. Both Gram-positive and Gram-negative bacteria communicate with their environment through exosome-like outer membrane vesicles. We demonstrated that mouse pups absorb exosomes from maternal milk and a fraction of milk exosomes (MEs) escapes absorption and reaches the large intestine. MEs altered the composition of bacterial communities in murine ceca. Hypothesis: MEs select genetic variations in gut bacteria, thereby contributing to the divergence of bacterial populations. Methods: Gut content was collected from the ceca of three mice, age 7 weeks, suspended in minimal salts media and divided into two aliquots. One aliquot was cultured in media containing a nutritionally relevant concentration of MEs (1.7x1010/mL; denoted ME-supplemented, MES) under anaerobic conditions for 7 days; the other aliquot was cultured in ME-free media (MEF). DNA was sequenced using a 75-bp single end protocol (Illumina NextSeq 500; estimated coverage 150x). Genetic variations were assessed by using the MIDAS and StrainPhlAn pipelines. Results: Bioinformatics analyses were performed by using 127,935,309±30,104,915 and 138,253,606±25,740,862 reads per sample in MES and MEF cultures, respectively (N=3). MIDAS: More than 200 and 190 million sequencing reads were mapped to 11 and 19 bacterial species in MES and MEF cultures, respectively. In MES cultures, 278 and 28,594 strain-level genetic variations were detected by high stringency (detected in all 3 cultures) and low stringency (detected in 2 out of 3 cultures) analyses, respectively. Ninety-five genes in 11 bacterial species carried non-synonymous SNPs in MES cultures in the high stringency dataset. In MEF cultures, 92 and 26,382 strain-level genetic variations were detected by high and low stringency analyses, respectively. Forty-two genes in 19 bacterial species carried non-synonymous SNPs in MEF cultures in the high stringency dataset. Genetic variations were detected in enzymes catalyzing essential steps in the metabolism of tryptophan, glutamate and purines, i.e., pathways implicated in neurotransmitter synthesis in the host. StrainPhlAn: We detected 6,715 genetic variations across all loci in E. faecalis, C. sporogenes and L. johnsonii for both MES and MEF combined, including 6,694 variations in protein coding regions: 5,182 non-synonymous (77%) and 1,512 synonymous (23%) variations. We detected 62 insertions and 75 deletions among the non-synonymous variations. Conclusions: MEs contribute to the divergence of gut bacteria through the selection of genetic variations, which might affect neuronal signaling in the host. Funding: NIFA/USDA 2016-67001-25301 and 2020-67017-30834, NIH P20GM104320, USDA Hatch and W-40022 and Gates Foundation OPP1200494. J.Z. is a consultant for PureTech Health, Inc.
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16S amplicon sequencing gives more reliable data for human milk microbiota studies than shotgun metagenomics sequencing
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16S amplicon sequencing gives more reliable data for human milk microbiota studies than shotgun metagenomics sequencing Johanne Spreckels1, Sanzhima Garmaeva1, Trishla Sinha1, Ranko Gacesa2, Alexander Kurilshikov1, Marloes Kruk1, Hiren Ghosh2, Hermie Harmsen3, Jingyuan Fu1,4, Alexandra Zhernakova1 1Department of Genetics, University Medical Center Groningen, Groningen, the Netherlands; 2Department of Gastroenterology and Hepatology, University Medical Center Groningen, Groningen, the Netherlands; 3Department of Medical Microbiology, University Medical Center Groningen, Groningen, the Netherlands; 4Department of Pediatrics, University Medical Center Groningen, Groningen, the Netherlands Background: Human milk microbes are important for the development of the infant gut microbiota and immune system. Many studies have investigated the milk microbiota using 16S amplicon (16S) sequencing, while only a few studies tried investigating the milk microbiome with whole metagenomics shotgun sequencing (MGS). Studying the human milk microbiome with MGS is challenging since milk contains a large number of human cells and only few microbes. Objective: We aimed to optimize milk sample preparation protocols to increase the amount and quality of microbial MGS data for human milk microbiome studies. Methods: DNA was isolated from a mock community, three human milk samples and negative controls with and without two different bacterial enrichment strategies (E1, E2) prior to DNA extraction, and subjected to 16S and MGS sequencing. Additionally, DNA was isolated from the same samples using four DNA extraction kits (A: MagMAX TNA Isolation Kit, B: DNeasy PowerSoil Pro Kit, C: Milk DNA Extraction Kit, D: QIAamp Fast DNA Stool Mini Kit) without enrichment and used the DNA for 16S sequencing. All isolations were performed in duplicates or triplicates. Results: All expected genera were detected in MGS and 16S sequencing data of mock communities isolated with the bacterial enrichment method E1. For mock samples prepared using the enrichment method E2, MGS library preparation was not successful, and only three of eight expected genera were detected when using 16S sequencing. The bacterial enrichment method E1 decreased both the percentage of microbial reads of the total number of MGS reads and the absolute number of microbial MGS reads in milk samples compared to samples prepared without enrichment. Even though similar bacterial genera were detected in most duplicates or triplicates of each milk sample, the detected genera were often found in negative controls as well, rendering the milk MGS data untrustworthy. Mock communities isolated without bacterial enrichment with the DNA isolation kits A-D and analyzed with 16S sequencing contained all expected bacterial genera, and kits A and B represented the true mock composition the best. The use of kits A and B also led to significantly lower 16S read numbers in negative controls than kits C and D. Both kits A and B identified bacteria commonly reported in human milk, and microbial profiles of the tested milk samples were similar with the two methods. Conclusion: Sample preparation and DNA isolation methods affect the results from milk microbiome studies. The tested bacterial enrichment methods do not improve milk MGS data and, also without bacterial enrichment, we cannot recommend the use of MGS to investigate the human milk microbiota. Instead, to study the human milk microbiota composition, we suggest DNA isolation with the MagMAX (A) or the PowerSoil Pro (B) kit and the use of 16S sequencing.
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Fetal gut colonization: meconium does not have a detectable microbiota before birth
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Fetal gut colonization: meconium does not have a detectable microbiota before birth Katherine M. Kennedy1,4, Max J. Gerlach2, Thomas Adam3, Markus M. Heimesaat4, Laura Rossi5,6, Michael G. Surette1,5,6, Deborah M. Sloboda1,6,7* and Thorsten Braun2* 1Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Canada 2Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Obstetrics and Department of 'Experimental Obstetrics', Berlin, Germany 3Labor Berlin, Charité Vivantes GmbH, Berlin, Germany 4Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute for Microbiology, Infectious Diseases and Immunology, Berlin, Germany 5Department of Medicine, McMaster University, Hamilton, Canada. 6Farncombe Family Digestive Health Research Institute, McMaster University, Hamilton, Canada 7Department of Pediatrics, McMaster University, Hamilton, Canada. *shared senior authorship Microbial colonization of the human intestine impacts host metabolism and immunity, however when colonization occurs is unclear. Although numerous studies have reported bacterial DNA in first-pass meconium samples, these samples are collected hours to days after birth. We investigated whether bacteria could be detected in meconium prior to birth. Fetal meconium (n = 20) was collected by rectal swab during elective breech Cesarean sections without labour prior to antibiotics and compared to technical and procedural controls (n = 5), first-pass meconium (neonatal meconium; n = 14), and infant stool (n = 25). Unlike first-pass meconium, no microbial signal distinct from negative controls was detected in fetal meconium by 16S rRNA gene sequencing. Additionally, positive aerobic (n = 10 of 20) and anaerobic (n = 12 of 20) clinical cultures of fetal meconium (13 of 20 samples positive in at least one culture) were identified as likely skin contaminants, most frequently Staphylococcus epidermidis, and not detected by sequencing in most samples (same genera detected by culture and sequencing in 2 of 13 samples with positive culture). We conclude that fetal gut colonization does not occur before birth, and that microbial profiles of neonatal meconium reflect populations acquired during and after birth.
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Gastrointestinal and Nasopharyngeal Microbiota profiles and Metabolomic changes over the course of lactation in Gambian mother/infant pairs up to 60 days of age
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Gastrointestinal and Nasopharyngeal Microbiota profiles and Metabolomic changes over the course of lactation in Gambian mother/infant pairs up to 60 days of age Authors Konstantinos Karampatsas1, Sean Aller1, Isabel Garcia Perez2, Alex Shaw2, Sora Liu2, Amadou Faal3, Mustapha Jaiteh3, Adam Witney1, Kirsty Le Doare1,2 Affiliations 1 St George’s, University of London, London, United Kingdom 2 Imperial College London, London, United Kingdom 3 Medical Research Council- The Gambia Unit, Fajara, The Gambia Background: Exclusive breastfeeding for the first 6 months of life is essential for infants’ healthy development. Microbiota composition in breastmilk affects intestinal microbiota colonisation and the development of the immune system in infants. The metabolomic content of breastmilk is thought to interact with the microbiota and thus may influence the developing infant immune system. Methods: In this study we characterised the microbiota of healthy, vaginally delivered, exclusively breastfed Gambian infants. 107 mothers and their infants were included in the study. We successfully sequenced 68 breast milk samples, 51 maternal rectovaginal swabs and 35 infants’ rectal swabs at birth. We also collected 70 breast milk samples and 51 infants’ nasopharyngeal swabs 60 days post-delivery. We used 16S rRNA gene sequencing to assess the microbiota composition and compare it between mothers and infants across the different body sites. After DNA extraction, 16S amplicon libraries were generated and sequenced. Taxonomic and functional analyses were then performed. Colostrum and mature breast milk samples also underwent metabolomic profiling using a multiplatform approach combining 1H nuclear magnetic resonance spectroscopy and Gas chromatography-mass spectrometry Results: Bacterial communities were distinct in breastmilk (BM), maternal rectovaginal swabs and infant rectal swabs, differing in both composition and diversity. BM composition changed over the first 60 days of lactation. The relative abundance of α-1,4- and α-1,3-Fucosylated HMOs increased over time. We found changes in 33 metabolites between birth and day 60 of life, such as monosaccharides, sugar alcohols and fatty acids known to be important for infant immunological, neurological, and gastrointestinal development, as well as being an important source of energy. Conclusions: The results of this study indicate that infant gut microbiota at birth is a unique bacterial community in transition. Breast milk microbiota composition and metabolomic profile change throughout lactation. These changes may contribute to the development of the infant microbiome according to the changing needs of the growing infant. Further studies are required to fully understand the interplay between the metabolome, microbiome and gut immunome to fully understand their role in infant gut immune development.
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An exploration into the role of the infant gut microbiome in Foetal Alcohol Spectrum Disorders (FASD)
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An exploration into the role of the infant gut microbiome in Foetal Alcohol Spectrum Disorders (FASD) Natasha Kitchin, Jacqueline S. Womersley, Andrea Engelbrecht, Anna-Susan Marais, Marlene M. de Vries, Philip A. May, Soraya Seedat and Sian M. J. Hemmings The prevalence of Foetal Alcohol Spectrum Disorders (FASD) in the Western Cape of South Africa is estimated to be between 20% and 28%, significantly higher than the global prevalence of 0.77%. Alcohol consumption compromises the integrity of the intestinal barrier thereby allowing bacteria to enter the bloodstream, and in doing so, be transported to the foetus. An altered maternal gut microbiome may influence foetal bacterial colonisation which may subsequently alter the functioning of the infant’s gut microbiota resulting in increased risk of developing a neurodevelopmental disorder. This study therefore aimed to compare the gut microbial composition of infants with and without FASD. Stool samples were collected from 211 infants (102 with FASD and 109 without FASD). 16S rRNA sequencing was performed on microbial DNA extracted from the stool samples. The dada2 pipeline was used to pre-process the fastq sequencing files, create an amplicon sequence variant table, and assign taxonomy. Differential compositional analyses were performed using PhyloSeq, while R was used to calculate diversity measures and compute the statistical analyses of microbial composition. There were no significant differences in alpha- or beta-diversity between infants diagnosed with FASD and those without FASD, however both delivery mode and Bristol Stool Scale influenced beta diversity. The infant gut microbiota was dominated by gram-negative anaerobes such as Prevotella and Bacteroides as well as Faecalibacterium to a lesser extent, with significant representations of gram-positive anaerobes such as Bifidobacterium and facultative microorganisms such as Eshcerichia/Shigella. Bifidobacterium was found to be significantly higher in infants diagnosed with FASD. A lower relative abundance of Bifidobacteria has been observed in children with Autism Spectrum Disorder (ASD), making this finding unexpected. Additionally, Prevotella was significantly higher in infants diagnosed with FASD. Although some articles have found a lower abundance of Prevotella in children with ASD, articles from other low- and middle-income countries have found higher levels of Prevotella in children with ASD. Of the less abundant genera, Rothia, Lactobacillus, Megasphaera, Catenibacterium and Holdemanella were found to be significantly higher in infants with FASD, while Pseudoflavonifracter, Morganella, Hungatella and Eisenbergiella were found to be significantly higher in infants without FASD. Although further studies are required, these findings are promising for microbe-based therapeutic interventions to reduce the extent of neurocognitive deficits and the debilitating symptoms associated with FASD.
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