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In this paper we describe our recent work in multi-excitation surface enhanced Raman spectroscopy (MX-SERS), and its application for robust strain-level bacteria identification. The development of MX-SERS follows directly from our previous work in rapid bacterial identification using multi-excitation Raman spectroscopy (MX-Raman), which enabled highly accurate (up to 99.75%) strain-level distinction of bacteria, including antibiotic resistant strains of bacteria and from within complex media. In this work we use the strong wavelength dependence of both the Raman scattering cross-section and the surface plasmon to demonstrate a novel capability in bacteria identification. Compared to MX-Raman, MX-SERS has up to 8x faster data acquisition speed as well as up to 4000x lower laser power incident on the sample. Furthermore, we fabricate SERS-active substrates with a simple and low-cost fabrication method that can be adapted to fit a chosen wavelength regime. This combination of strain-level sensitivity and high-speed detection, combined with a low-cost SERS substrate, has strong potential applications in clinical diagnostics, and could be integrated within a real-world pathogen detection workflow. This presents new capabilities in label-free bacterial detection including novel culture-free investigation capabilities, and an improved methodology for sample handling with minimal preparation and processing.

Current methods for diagnosing acute and complex infections mostly rely on culture-based methods and, for biofilms, fluorescencein-situhybridization. These techniques are labor-intensive and can take 2-4 days to return a test result, especially considering an extra culturing step required for the antibiotic susceptibility testing (AST). This places a significant burden on healthcare providers, delaying treatment and leading to adverse patient outcomes. Here, we report the complementary use of our newly developed multi-excitation Raman spectroscopy (ME-RS) method with whole-genome sequencing (WGS). Four WHO priority pathogens are AST phenotyped and their antimicrobial resistance (AMR) profile determined by WGS. On application of ME-RS method we find high correlation with the WGS characterization. Highly accurate classification based on the species (98.93%), wild-type/non-wild type (99.45%), and presence or absence of thick peptidoglycan layers in cell walls (100%), as well as at the individual strain level (99.29%). These results clearly demonstrate the potential of ME-RS as a rapid and first-stage tool for species, resistance and strain-level classification which can be followed up by WGS for confirmation. Such a workflow can facilitate efficient antimicrobial stewardship to handle and prevent the spread of AMR.

Rapid bacterial identification and antimicrobial resistance gene (ARG) detection are crucial for fast optimization of antibiotic treatment, especially for septic patients where each hour of delayed antibiotic prescription might have lethal consequences. This work investigates whether the Oxford Nanopore Technology’s (ONT) Flongle sequencing platform is suitable for real-time sequencing directly from blood cultures to identify bacteria and detect resistance-encoding genes. For the analysis, we used pure bacterial cultures of four clinical isolates of Escherichia coli and Klebsiella pneumoniae and two blood samples spiked with either E. coli or K. pneumoniae that had been cultured overnight. We sequenced both the whole genome and plasmids isolated from these bacteria using two different sequencing kits. Generally, Flongle data allow rapid bacterial ID and resistome detection based on the first 1,000–3,000 generated sequences (10 min to 3 h from the sequencing start), albeit ARG variant identification did not always correspond to ONT MinION and Illumina sequencing-based data. Flongle data are sufficient for 99.9% genome coverage within at most 20,000 (clinical isolates) or 50,000 (positive blood cultures) sequences generated. The SQK-LSK110 Ligation kit resulted in higher genome coverage and more accurate bacterial identification than the SQK-RBK004 Rapid Barcode kit.

Graphical abstract, Antibiotic resistance poses a major threat to public health. More effective ways of the antibiotic prescription are needed to delay the spread of antibiotic resistance. Employment of sequencing technologies coupled with the use of trained neural network algorithms for genotype-to-phenotype prediction will reduce the time needed for antibiotic susceptibility profile identification from days to hours. In this work, we have sequenced and phenotypically characterized 171 clinical isolates of Escherichia coli and Klebsiella pneumoniae from Norway and India. Based on the data, we have created neural networks to predict susceptibility for ampicillin, 3rd generation cephalosporins and carbapenems. All networks were trained on unassembled data, enabling prediction within minutes after the sequencing information becomes available. Moreover, they can be used both on Illumina and MinION generated data and do not require high genome coverage for phenotype prediction. We cross-checked our networks with previously published algorithms for genotype-to-phenotype prediction and their corresponding datasets. Besides, we also created an ensemble of networks trained on different datasets, which improved the cross-dataset prediction compared to a single network. Additionally, we have used data from direct sequencing of spiked blood cultures and found that AMR-Diag networks, coupled with MinION sequencing, can predict bacterial species, resistome, and phenotype as fast as 1–8 h from the sequencing start. To our knowledge, this is the first study for genotype-to-phenotype prediction: (1) employing a neural network method; (2) using data from more than one sequencing platform; and (3) utilizing sequence data from spiked blood cultures.

Spore forming bacteria comprise a large part of the human gut microbiota. However, study of the endospores in gut microbiota is limited due to difficulties of culturing and numerous unknown germination factors. In this study we propose a new method for culture-independent characterization of endospores in stool samples. We have enriched DNA of spore-forming bacterial species from stool samples of 40 mother-child pairs from a previously described mother-child cohort. The samples were exposed to a two-step purification process comprising ethanol and ethidium monoazide (EMA) treatment to first kill vegetative cells and to subsequently eliminate their DNA from the samples. The composition of the ethanol-EMA resistant DNA was characterized by 16S rRNA marker gene sequencing. Operational taxonomic units (OTUs) belonging to the Clostridia class (OTU1: Romboutsia, OTU5: Peptostreptococcaceae and OTU14: Clostridium senso stricto) and one belonging to the Bacillus class (OTU20: Turicibacter) were significantly more abundant in the samples from mothers and children after ethanol-EMA treatment than in those treated with ethanol only. No correlation was observed between ethanol-EMA resistant OTUs detected in children and in their mothers, which indicates that a low level of spore-forming species are shared between mothers and their children. Anaerobic ethanol-resistant bacteria were isolated from all mothers and all children over 1 year of age. Generally, in 70% of the ethanol-treated samples used for anaerobic culturing, 16S rRNA gene sequences of bacterial isolates corresponded to OTUs detected in these samples after EMA treatment. We report a new DNA-based method for the characterization of endospores in gut microbiota. Our method has high degree of correspondence to the culture-based method, although it requires further optimization. Our results also indicate a high turnover of endospores in the gut during the first two years of life, perhaps with a high environmental impact. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Bloodstream infections (BSI) and sepsis are major causes of morbidity and mortality worldwide. Blood culture-based diagnostics usually requires 1–2 days for identification of bacterial agent and an additional 2–3 days for phenotypic determination of antibiotic susceptibility pattern. With the escalating burden of antimicrobial resistance (AMR) rapid diagnostics becomes increasingly important to secure adequate antibiotic therapy. Real-time whole genome sequencing represents a genotypic diagnostic approach with the ability to rapidly identify pathogens and AMR-encoding genes. Here we have used nanopore sequencing of bacterial DNA extracted from positive blood cultures for identification of pathogens, detection of plasmids and AMR-encoding genes. To our knowledge, this is the first study to gather the above-mentioned information from nanopore sequencing and conduct a comprehensive analysis for diagnostic purposes in real-time. Identification of pathogens was possible after 10 minutes of sequencing and all predefined AMR-encoding genes and plasmids from monoculture experiments were detected within one hour using raw nanopore sequencing data. Furthermore, we demonstrate the correct identification of plasmids and blaCTX-M subtypes using de novo assembled nanopore contigs. Results from this study hold great promise for future applications in clinical microbiology and for health care surveillance purposes.

Breastfeeding is one of the major factors affecting the early development of the infant gut microbiota, and weaning is associated with a shift in the gut microbiota toward a more adult composition. Through breastfeeding, infants receive bioactive components that shape their microbiota while also being exposed to the breast milk and breast surface microbial communities. Recent studies have suggested the possibility of an entero-mammary route of microbial transfer, opening the possibility of infant gut microbiota modulation through maternal probiotic supplementation. In this study, we have analyzed breast milk samples collected at 10 d and 3 mo postpartum from women participating in the Probiotics in the Prevention of Allergy among Children in Trondheim placebo controlled trial. Women who were randomized to the probiotic arm of the Probiotics in the Prevention of Allergy among Children in Trondheim trial received a fermented milk supplemented with Lactobacillus rhamnosus GG, Lactobacillus acidophilus La-5, and Bifidobacterium animalis ssp. lactis Bb-12, consuming this daily from 4 wk before their expected due date until 3 mo after birth. In total, 472 breast milk samples were assessed for the administered bacteria using quantitative real-time PCR and the microbiota transferred during breastfeeding was analyzed using 16S ribosomal RNA gene sequencing of 142 samples. We found that breastfeeding is unlikely to be a significant source of L. rhamnosus GG, L. acidophilus La-5, and B. animalis ssp. lactis Bb-12 for infants in the probiotic arm of the trial. Furthermore, maternal supplementation did not significantly affect the overall composition of the breast milk microbiota transferred during breastfeeding. We also present a descriptive analysis of this microbiota, which was largely dominated by Streptococcus and Staphylococcus genera at both 10 d and 3 mo postpartum. Samples collected at 3 mo postpartum had a statistically significant lower presence and relative abundance of the Staphylococcus genus. These samples also had a greater number of observed species and diversity, including more operational taxonomic units from the Rothia, Veillonella, Granulicatella, and Methylbacterium genera. © 2018, THE AUTHORS. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association ® . This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

The purpose of this study was to explore the microbiota of Norwegian fermented fish (rakfisk), a traditional product popular in the Norwegian market. Brine samples, collected from six producers during two subsequent years, were used. The producers applied different salt concentrations (between 3.8% and 7.2% NaCl), ripening temperatures (between 3.5 and 7.5 &deg, C), fish species (trout or char), and fish upbringing (wild trout, on-shore farmed trout or char, and off-shore farmed char). The microbiota in the brine during the ripening process was mainly characterized by DNA-based, culture-independent methods. In total, 1710 samples were processed and of these 1342 were used for the final analysis. The microbiota was dominated by Gammaproteobacteria and Bacilli with the largest variance between samples associated with the genera Psychrobacter and Lactobacillus. The variance in the material was mainly determined by the origin of the samples, i.e., the different producers. The microbiota from the individual producers was to a large extent reproducible from one year to the next and appeared to be determined by the relatively small differences in the salinity and the ripening temperature. This is the first study exploring the microbiota in rakfisk brine and it provides insights into environmental factors affecting the rakfisk ecosystems.

Transition from an infant to an adult associated gut microbiota with age through establishment of strict anaerobic bacteria remains one of the key unresolved questions in gut microbial ecology. Here a comprehensive comparative analysis of stool microbiota in a large cohort of mothers and their children sampled longitudinally up until 2 years of age using sequencing analysis tool was presented that allows realistic microbial diversity estimates. In this work, evidence for the switch from children to adult associated microbial profile between 1 and 2 years of age was provided, suggestively driven by Bifidobacterium breve. An Operational Taxonomic Unit (OTU) belonging to B. breve was highly prevalent in the population throughout the first year of life, and was negatively associated with detection of a range of adult-like OTUs. Although an adult profile was not fully established by 2 years of age, it was demonstrated that with regards to the most prevalent OTUs, their prevalence in the child population by then already resembled that of the adult population. Taken together, it was proposed that late-colonizing OTUs were recruited at a later stage and were not acquired at birth with the recruitment being controlled by gatekeeping OTUs until the age of 1 year.

The maternal microbiota plays an important role in infant gut colonization. In this work we have investigated which bacterial species are shared across the breast milk, vaginal and stool microbiotas of 109 women shortly before and after giving birth using 16S rRNA gene sequencing and a novel reduced metagenomic sequencing (RMS) approach in a subgroup of 16 women. All the species predicted by the 16S rRNA gene sequencing were also detected by RMS analysis and there was good correspondence between their relative abundances estimated by both approaches. Both approaches also demonstrate a low level of maternal microbiota sharing across the population and RMS analysis identified only two species common to most women and in all sample types (Bifidobacterium longum and Enterococcus faecalis). Breast milk was the only sample type that had significantly higher intra- than inter- individual similarity towards both vaginal and stool samples. We also searched our RMS dataset against an in silico generated reference database derived from bacterial isolates in the Human Microbiome Project. The use of this reference-based search enabled further separation of Bifidobacterium longum into Bifidobacterium longum ssp. longum and Bifidobacterium longum ssp. infantis. We also detected the Lactobacillus rhamnosus GG strain, which was used as a probiotic supplement by some women, demonstrating the potential of RMS approach for deeper taxonomic delineation and estimation. © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Use of the 16S rRNA gene in microbiota studies is limited by the lack of taxonomic and functional resolution. High resolution analyses are particularly important for understanding transmission and persistence of bacteria. The aim of our work was therefore to compare a novel reduced metagenome sequencing (RMS) approach with 16S rRNA gene sequencing to determine both the metagenome genetic diversity and the mother-to-child sharing of the microbiota in a cohort of 17 mother-child pairs. We found that although both approaches gave comparable results with respect to sample separation and taxonomy, RMS gave higher resolution and the potential for genomic-/functional assignment. Using RMS we estimated that the metagenome size increased from about 60 Mbp for 4-day-old children to about 225 Mbp for mothers. The 4-day-old children shared 7% of the metagenome sequences with the mothers, while the metagenome sequence sharing was >30% among the mothers. We found 15 genomes shared across >50% of the mothers, of which 10 belonged to Clostridia. Only Bacteroides showed a direct mother-child association, with B. vulgatus being abundant in both 4-day-old children and mothers. For the functional assignments, we identified a significant association between antibiotic usage during labor, and quantity of Fosfomycin resistance genes. In conclusion, our results show a higher functional and taxonomic resolution for RMS compared to 16S rRNA gene sequencing, where RMS enabled a detailed description of mother to child gut microbiota transmission – supporting a late recruitment of most gut bacteria and an effect of antibiotic treatment during labor on infant antibiotic resistance gene patterns.

Maternal probiotic supplementation has been shown to prevent the development of atopic dermatitis in the offspring. We aimed to investigate whether probiotics in pregnant and breast-feeding mothers altered the colonization pattern and the diversity of the mothers' and children's intestinal microbiota.In a randomized, double-blind trial, women received probiotic milk or placebo from 36 weeks of gestation up to 3 months postnatally while breast-feeding. The probiotic milk contained Lactobacillus rhamnosus GG, L acidophilus La-5, and Bifidobacterium animalis subsp. lactis Bb-12. Stool samples were collected from the mothers at 30 to 36 weeks of gestation and 3 months after birth, and from the child at age 10 days, 3 months, 1 year, and 2 years, and bacteria were analyzed by quantitative polymerase chain reaction. Additionally, stool samples from 3-month-old and 2-year-old children were characterized using 16S ribosomal RNA gene deep sequencing to estimate the bacterial classes and genera, and the α- and β-diversity.Three months after birth, both the prevalence and the relative abundance of the administered probiotic bacteria were significantly increased among the mothers in the probiotic group compared with among those in the placebo group. Only the Lactobacillus rhamnosus GG bacteria colonized the children at 10 days and at 3 months of age. There were no significant differences in the abundance of the administered probiotic bacteria between the groups at 1 and 2 years of age. For the bacterial classes and genera, and α- and β-diversity, there were no significant differences between the groups.Different probiotic bacteria seem to have different ability to transfer from the mother to the child. We found no evidence that the probiotics altered the microbial composition or α- and β-diversity of the children.

We still do not know the main patterns of prokaryote evolution. This is due to the antiquity of these events, as well as major non-linear differences in evolutionary rates among lineages and within different sequence positions, in addition to horizontal gene transfer. Here, we addressed prokaryotic evolutionary patterns using the simple approach of determining whether there are pairwise 16S rRNA gene sequence distances that are over-represented on average in current reference databases. Our rationale was that, despite major differences in evolutionary rates, the average rate among all lineages would reflect the history of speciation events. Using an alignment-independent approach, we identified three Euclidean distances being over-represented in the Greengenes 97 % identity database. Taxonomic assignments of these distances showed that they corresponded to the family, phylum and kingdom levels, respectively. Therefore, we propose that these taxonomic levels correspond to ancient speciation events.

Understanding the transmission of the human microbiota from mother to child is of major importance. Although we are gaining knowledge using 16S rRNA gene analyses, the resolution of this gene is not sufficient to determine transmission patterns. We therefore developed an Illumina deep sequencing approach targeting the 16-23S rRNA Internal Transcribed Spacer (ITS) for high-resolution microbiota analyses. Using this approach, we analyzed the composition and potential mother to child transmission patterns of the microbiota (milk and stool) in a longitudinal cohort of 20 mother/child pairs. Our results show overlap in the infant stool microbiota with both mother's milk and stool, and that the overlap with stool increases with age. We found an Operational Taxonomic Unit resembling Streptococcus gordonii as the most widespread colonizer of both mothers and their children. In conclusion, the increased resolution of 16-23S rRNA ITS deep sequencing revealed new knowledge about potential transmission patterns of human-associated bacteria.

We use a novel multidimensional searching approach to present the first exhaustive search for all possible repeated sequences in 166 genomes selected to cover the bacterial domain. We found an overrepresentation of repeated sequences in all but one of the genomes. The most prevalent repeats by far were related to interspaced short palindromic repeats (CRISPRs) — conferring bacterial adaptive immunity. We identified a deep branching clade of thermophilic Firmicutes containing the highest number of CRISPR repeats. We also identified a high prevalence of tandem repeated heptamers. In addition, we identified GC-rich repeats that could potentially be involved in recombination events. Finally, we identified repeats in a 16322 amino acid mega protein (involved in biofilm formation) and inverted repeats flanking miniature transposable elements (MITEs). In conclusion, the exhaustive search for repeated sequences identified new elements and distribution of these, which has implications for understanding both the ecology and evolution of bacteria.

We evaluated bead-beating cell-lysis in analysing the human stool metagenome, since this is a key step. We observed that two different bead-beating instruments from the same producer gave a three-fold difference in the Bacteroidetes to Firmicutes ratio. This illustrates that bead-beating can have a major impact on downstream metagenome analyses.

The genetic diversity and sharing of the mother-child associated microbiota remain largely unexplored. This severely limits our functional understanding of gut microbiota transmission patterns. The aim of our work was therefore to use a novel reduced metagenome sequencing in combination with shotgun and 16S rRNA gene sequencing to determine both the metagenome genetic diversity and the mother-to-child sharing of the microbiota. For a cohort of 17 mother-child pairs we found an increase of the collective metagenome size from about 100 Mbp for 4-day-old children to about 500 Mbp for mothers. The 4-day-old children shared 7% of the metagenome sequences with the mothers, while the metagenome sequence sharing was more than 30% among the mothers. We found 15 genomes shared across more than 50% of the mothers, of which 10 belonged to Clostridia. Only Bacteroides showed a direct mother-child association, with B. vulgatus being abundant in both 4-day-old children and mothers. In conclusion, our results support a common pool of gut bacteria that are transmitted from adults to infants, with most of the bacteria being transmitted at a stage after delivery.

The association of a DNA profile with a certain body fluid can be of essential importance in the evaluation of biological evidence. Several alternative methods for body fluid prediction have been proposed to improve the currently used presumptive tests. Most of them measure gene expression. Here we present a novel approach based on microbial taxonomic profiles obtained by standard 16S rRNA gene sequencing. We used saliva deposited on skin as a forensically relevant study model, but the same principle can be applied for predicting other bacteria rich body fluids. For classification we used standard pattern recognition based on principal component analysis in combination with linear discriminant analysis. A cross-validation of the experimental data shows that the new method is able to successfully classify samples from saliva deposited on skin and samples from pure skin in 94% of the cases. We found that there is a person-effect influencing the result, especially from skin, indicating that a reference sample of pure skin microbiota from the same person could improve accuracy. In addition the pattern recognition methods could be further optimized. Although there is room for improvement, this study shows the potential of microbial profiles as a new forensic tool for body fluid prediction.

Background The fungi in the gastrointestinal tract, the gut mycobiota, are now recognised as a significant part of the gut microbiota, and they may be important to human health. In contrast to the adult gut mycobiota, the establishment of the early gut mycobiota has never been described, and there is little knowledge about the fungal transfer from mother to offspring. Methods In a prospective cohort, we followed 298 pairs of healthy mothers and offspring from 36 weeks of gestation until 2 years of age (1516 samples) and explored the gut mycobiota in maternal and offspring samples. Half of the pregnant mothers were randomised into drinking probiotic milk during and after pregnancy. The probiotic bacteria included Lactobacillus rhamnosus GG (LGG), Bifidobacterium animalis subsp. lactis Bb-12 and Lactobacillus acidophilus La-5. We quantified the fungal abundance of all the samples using qPCR of the fungal internal transcribed spacer (ITS)1 segment, and we sequenced the 18S rRNA gene ITS1 region of 90 high-quantity samples using the MiSeq platform (Illumina). Results The gut mycobiota was detected in most of the mothers and the majority of the offspring. The offspring showed increased odds of having detectable faecal fungal DNA if the mother had detectable fungal DNA as well (OR = 1.54, p = 0.04). The fungal alpha diversity in the offspring gut increased from its lowest at 10 days after birth, which was the earliest sampling point. The fungal diversity and fungal species showed a succession towards the maternal mycobiota as the child aged, with Debaryomyces hansenii being the most abundant species during breast-feeding and Saccharomyces cerevisiae as the most abundant after weaning. Probiotic consumption increased the gut mycobiota abundance in pregnant mothers (p = 0.01). Conclusion This study provides the first insight into the early fungal establishment and the succession of fungal species in the gut mycobiota. The results support the idea that the fungal host phenotype is transferred from mother to offspring. Trial registration Clinicaltrials.gov NCT00159523

Vaginal microbiota is an important early source of bacterial colonization for newborns. However, only a few small studies have investigated the composition of vaginal microbiota during labor. In this work, we analyzed vaginal swabs collected at 36 weeks gestation and at the onset of labor from 256 women participating in a randomized placebo-controlled study of probiotic supplementation for the prevention of atopic dermatitis in offspring. Although individuals’ vaginal microbiota was stable over time, several bacterial families, which are characteristic of mixed community state type (CST) IV, were overrepresented in vaginal swabs sampled at labor. Alpha-diversity also tended to increase by between 36 weeks gestation and the onset of birth. In the majority of women, CST remained the same throughout the study. Among the women who switched their vaginal microbiota from one CST to another, approximately half shifted towards CST IV. Although CST IV is often associated with bacterial vaginosis, which in turn may lead to preterm birth, in our cohort this shift was not associated with self-reported vaginosis, preterm delivery or birthweight. Probiotic consumption did not alter vaginal microbiota. © The Author(s) 2017. This article is licensed under a Creative Commons Attribution 4.0 International License.

The human intestinal microbiota plays a major beneficial role in immune development and resistance to pathogens. The use of antibiotics, however, can cause the spread of antibiotic resistance genes within the resident intestinal microbiota. Important vectors for this are integrons. This review therefore focuses on the integrons in non-pathogenic bacteria as a potential source for the development and persistence of multidrug resistance. Integrons are a group of genetic elements which are assembly platforms that can capture specific gene cassettes and express them. Integrons in pathogenic bacteria have been extensively investigated, while integrons in the intestinal microbiota have not yet gained much attention. Knowledge of the integrons residing in the microbiota, however, can potentially aid in controlling the spread of antibiotic resistance genes to pathogens.

A key message from a range of high profile next generation sequencing studies on the human microbiota is that it composes a tremendously rich community of more than 1000 species within each one of us. Although more recent studies have shown estimates of between 100 and 200 species per individual, this has not yet been made clear in the literature. Currently, the most widely accepted estimate of species richness is therefore five to ten times too high. Here, we will review the different estimates of species richness in the literature, address potential sources of artefacts, the reluctance to correct these, and provide suggestions for future directions.

Bifidobacteria are a major microbial component of infant gut microbiota, which is believed to promote health benefits for the host and stimulate maturation of the immune system. Despite their perceived importance, very little is known about the natural development of and possible correlations between bifidobacteria in human populations. To address this knowledge gap, we analyzed stool samples from a randomly selected healthy cohort of 87 infants and their mothers with >90% of vaginal delivery and nearly 100% breast-feeding at 4 months. Fecal material was sampled during pregnancy, at 3 and 10 days, at 4 months, and at 1 and 2 years after birth. Stool samples were predicted to be rich in the species Bifidobacterium adolescentis, B. bifidum, B. dentium, B. breve, and B. longum. Due to high variation, we did not identify a clear age-related structure at the individual level. Within the population as a whole, however, there were clear age-related successions. Negative correlations between the B. longum group and B. adolescentis were detected in adults and in 1- and 2-year-old children, whereas negative correlations between B. longum and B. breve were characteristic for newborns and 4-month-old infants. The highly structured age-related development of and correlation networks between bifidobacterial species during thefirst 2 years of life mirrors their different or competing nutritional requirements, which in turn may be associated with specific biological functions in the development of healthy gut. M other-to-child transmission and temporal development of the human gut microbiota are population-based processes. Understanding these processes is essential to the identification of gutmicrobiota-associatedfunctionalities.Certainmembersofthe genusBifidobacteriumrepresentveryabundantearlycolonizersof the infant gut (1), making them a prime target for investigation. The high abundance of Bifidobacterium species in infants is considered to promote development and maturation of the immune system to sustain health (2‐4). Furthermore, our recent studies suggest that the succession of bifidobacteria is important for the proper immunological development (5, 6). Eight Bifidobacterium species have been associated with the human gastrointestinal tract (GIT): Bifidobacterium adolescentis, B. breve, B. longum subsp. longum, B. longum subsp. infantis, B. pseudolongum,B.bifidum,B.pseudocatenulanum,andB.dentium. Some bifidobacterial strains, e.g., B. pseudolongum, appear to be exclusively associated with adult gut microbiota, and some, especially B. longum subsp. infantis, are typically isolated from infants (7). The population-wise, age-related development of bifidobacteria in infants remains to be investigated. Due to the fact that there is evidence for previously uncharacterized diversity of bifidobacteria in the human gut (8, 9), we believe that to obtain a comprehensive description of bifidobacterial composition, the study should include a large number of individuals, and various techniques should be applied. It is also veryimportanttoavoidtargetingspecificbifidobacteria,sincethis may lead to the exclusion of as-yet-undiscovered, but potentially important bifidobacterial groups. The aim of the present study, therefore, was to describe bifidobacterial composition, temporal development, and possible correlationsinalarge,randomlyselectedcohortofmothersandtheir children using a combination of both culture-dependent and -independent techniques. This was done by analyzing the series of stool samples from the IMPACT cohort (10). The samples were collected during early and late pregnancy stages and at 3 days, 10 days, 4 months, and 1 and 2 years after birth. We present results showing a highly structured, age-related succession of bifidobacterial species within the study population, as well as correlations between the abundances of these species during thefirst 2 years of life.

We addressed the challenges of analyzing next-generation 16S rRNA gene deep sequencing data from the uncharacterized microbial majority. This was performed using a novel de novo semi-alignment approach. The semi-alignments were based on Orthologous Tri-Nucleotides (OTNs), which are identical trinucleotides located in the same sequence region. OTNs in high error homopolymeric tracts were excluded to avoid overestimation of genetic distances. Phylogenetic information was derived assuming an exponential decay in shared OTNs between pairs of bacteria. OTN relatedness was also explored through principal component analysis (PCA). In evaluating the OTN approach we reanalyzed a dataset consisting of triplicate GS FLX titanium pyrosequencing runs for each of two experimental soil samples, in addition to analyses of the Greengenes core dataset. The conclusion from these comparisons was that the OTN approach was superior to traditional alignments both with respect to speed and accuracy. We therefore believe that our OTN-based semi-alignment approach will be a valuable contribution to future exploration of deep sequencing data.

Knowledge on dynamic interactions in microbiota is pivotal for understanding the role of bacteria in the gut. We herein present comprehensive dynamic models of the horse cecal microbiota, which include short-chained fatty acids, carbohydrate metabolic networks, and taxonomy. Dynamic models were derived from time-series data in a crossover experiment in which four cecum-cannulated horses were fed a starch-rich diet of hay supplemented with barley (starch intake 2 g kg−1 body weight per day) and a fiber-rich diet of only hay. Cecal contents were sampled via the cannula each h for 24 h for both diets. We observed marked differences in the microbial dynamic interaction patterns for Fibrobacter succinogenes, Lachnospiraceae, Streptococcus, Treponema, Anaerostipes, and Anaerovibrio between the two diet groups. Fluctuations and microbiota interactions were the most pronounced for the starch rich diet, with Streptococcus spp. and Anaerovibrio spp. showing the largest fluctuations. Shotgun metagenome sequencing revealed that diet differences may be explained by modular switches in metabolic cross-feeding between microbial consortia in which fermentation is linked to sugar alcohols and amino sugars for the starch-rich diet and monosaccharides for the fiber-rich diet. In conclusion, diet may not only affect the composition of the cecal microbiota, but also dynamic interactions and metabolic cross-feeding. Knowledge on dynamic interactions in microbiota is pivotal for understanding the role of bacteria in the gut. We herein present comprehensive dynamic models of the horse cecal microbiota, which include short-chained fatty acids, carbohydrate metabolic networks, and taxonomy. Dynamic models were derived from time-series data in a crossover experiment in which four cecum-cannulated horses were fed a starch-rich diet of hay supplemented with barley (starch intake 2 g kg–1 body weightper day) and a fiber-rich diet of only hay. Cecal contents were sampled via the cannula each h for 24 h for both diets. We observed marked differences in the microbial dynamic interaction patterns for Fibrobacter succinogenes, Lachnospiraceae, Streptococcus, Treponema, Anaerostipes, and Anaerovibrio between the two diet groups. Fluctuations and microbiota interactions were the most pronounced for the starch rich diet, with Streptococcus spp. and Anaerovibrio spp. showing the largest fluctuations. Shotgun metagenome sequencing revealed that diet differences may be explained by modular switches in metabolic cross-feeding between microbial consortia in which fermentation is linked to sugar alcohols and amino sugars for the starch-rich diet and monosaccharides for the fiber-rich diet. In conclusion, diet may not only affect the composition of the cecal microbiota, but also dynamic interactions and metabolic cross-feeding.

Although a link between probiotic intervention and reduction in atopic disease has been documented, no consistent associations with microbiota has yet been established. Here we have conducted an extensive analysis of the microbiota from more than 250 mother child pairs from a probiotic intervention cohort, where we previously have shown 40 % reduction in atopic dermatitis. Within the probiotic intervention group at the age of 10 days we found that the atopic children had a deviating microbiota (p = 0.028, BH-FDR corrected Kruskal Wallis) with high levels (> 10 %) of a bacterium related to Bifidobacterium dentium (p=0.039, BHFDR corrected Chi-square). Based on these findings, we propose a model with two groups of children where the group responding to probiotic intervention, has gut microbiota related to that of non-atopic children; while the non-responding group has a divergent microbiota at the age of 10 days with overrepresented amounts of B. dentium. In conclusion, our results support the importance of early colonization for prevention of diseases developing later in life, with potential intervention effects being dependent on the intrinsic microbiota.

OBJECTIVE HIV-1 infection is characterized by altered intestinal barrier, gut microbiota dysbiosis, and systemic inflammation. We hypothesized that changes of the gut microbiota predict immune dysfunction and HIV-1 progression, and that antiretroviral therapy (ART) partially restores the microbiota composition. DESIGN An observational study including 28 viremic patients, three elite controllers, and nine uninfected controls. Blood and stool samples were collected at baseline and for 19 individuals at follow-up (median 10 months) during ART. METHODS Microbiota composition was determined by 16S rRNA sequencing (Illumina MiSeq). Soluble markers of microbial translocation and monocyte activation were analyzed by Limulus Amebocyte Lysate assay or ELISA. RESULTS Several alpha-diversity measures, including number of observed bacterial species and Shannon index, were significantly lower in viremic patients compared to controls. The alpha diversity correlated with CD4 T-cell counts and inversely with markers of microbial translocation and monocyte activation. In multivariate linear regression, for every age and sex-adjusted increase in the number of bacterial species, the CD4 T-cell count increased with 0.88 (95% confidence interval 0.35-1.41) cells/μl (P = 0.002). After introduction of ART, microbiota alterations persisted with further reduction in alpha diversity. The microbiota composition at the genus level was profoundly altered in viremic patients, both at baseline and after ART, with Prevotella reduced during ART (P < 0.007). CONCLUSIONS Gut microbiota alterations are closely associated with immune dysfunction in HIV-1 patients, and these changes persist during short-term ART. Our data implicate that re-shaping the microbiota may be an adjuvant therapy in patients commencing successful ART.

Honey bees (Apis mellifera) are prominent crop pollinators and are, thus, important for effective food production. The honey bee gut microbiota is mainly host specific, with only a few species being shared with other insects. It currently remains unclear how environmental/dietary conditions affect the microbiota within a honey bee population over time. Therefore, the aim of the present study was to characterize the composition of the midgut/pyloric microbiota of a honey bee apiary throughout a season. The rationale for investigating the midgut/pyloric microbiota is its dynamic nature. Monthly sampling of a demographic homogenous population of bees was performed between May and October, with concordant recording of the honey bee diet. Mixed Sanger-and Illumina 16S rRNA gene sequencing in combination with a quantitative PCR analysis were used to determine the bacterial composition. A marked increase in α-diversity was detected between May and June. Furthermore, we found that four distinct phylotypes belonging to the Proteobacteria dominated the microbiota, and these displayed major shifts throughout the season. Gilliamella apicola dominated the composition early on, and Snodgrassella alvi began to dominate when the other bacteria declined to an absolute low in October. In vitro co-culturing revealed that G. apicola suppressed S. alvi. No shift was detected in the composition of the microbiota under stable environment/dietary conditions between November and February. Therefore, environmental/dietary changes may trigger the shifts observed in the honey bee midgut/pyloric microbiota throughout a season.

Background: Westernized lifestyle and hygienic behavior have contributed to dramatic changes in the human-associated microbiota. This particularly relates to indoor activities such as house cleaning. We therefore investigated the associations between washing and vacuum cleaning frequency and the gut microbiota composition in a large longitudinal cohort of mothers and their children. The gut microbiota composition was determined using 16S ribosomal RNA (rRNA) gene Illumina deep sequencing. Results: We found that high vacuum cleaning frequency about twice or more a week was associated with an altered gut microbiota composition both during pregnancy and for 2-year-old children, while there were no associations with house washing frequency. In total, six Operational Taxonomic Units (OTUs) showed significant False Discovery Rate (FDR) corrected associations with vacuum cleaning frequency for mothers (two positive and four negative) and five for 2-year-old children (four positive and one negative). For mothers and the 2-year-old children, OTUs among the dominant microbiota (average >5 %) showed correlation to vacuum cleaning frequency, with an increase in Faecalibacterium prausnitzii for mothers (p = 0.013, FDR corrected), and Blautia sp. for 2-year children (p = 0.012, FDR corrected). Conclusions: Bacteria showing significant associations are among the dominant gut microbiota, which may indicate indirect immunomodulation of the gut microbiota possibly through increased allergen (dust mites) exposure as a potential mechanism. However, further exploration is needed to unveil mechanistic details. © 2015 Avershina et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Despite the importance, the diversity of the human infant gut microbiota still remains poorly characterized at the regional scale. Here, we investigated the faecal microbiota diversity in a large 16S rRNA gene data set from a healthy cohort of 86 mothers and their children from the Trondheim region in Norway. Samples were collected from mothers during early and late pregnancy, as well as from their children at 3 days, 10 days, 4 months, 1 year and 2 years of age. Using a combination of Sanger sequencing of amplicon mixtures (without cloning), real-time quantitative PCR and deep pyrosequencing, we observed a clear age-related colonization pattern in children that was surprisingly evident between 3- and 10-day samples. In contrast, we did not observe any shifts in microbial composition during pregnancy. We found that alpha-diversity was highest at 2 years and lowest at 4 months, whereas beta-diversity estimates indicated highest interindividual variation in newborns. Variation significantly decreased by the age of 10 days and was observed to be convergent over time; however, there were still major differences between 2 years and adults whom exhibited the lowest interindividual diversity. Taken together, the major age-affiliated population shift within gut microbiota suggests that there are important mechanisms for transmission and persistence of gut bacteria that remain unknown. © The Author 2013; all rights reserved. Published by Oxford University Press on behalf of the Federation of European Microbiological Societies. This is the authors' accepted and refereed manuscript to the article.

Background Depression is a chronic syndrome with a pathogenesis linked to various genetic, biological, and environmental factors. Several links between gut microbiota and depression have been established in animal models. In humans, however, few correlations have yet been demonstrated. The aim of our work was therefore to identify potential correlations between human fecal microbiota (as a proxy for gut microbiota) and depression. Methods We analyzed fecal samples from 55 people, 37 patients, and 18 non-depressed controls. Our analyses were based on data generated by Illumina deep sequencing of 16S rRNA gene amplicons. Key Results We found several correlations between depression and fecal microbiota. The correlations, however, showed opposite directions even for closely related Operational Taxonomic Units (OTU's), but were still associated with certain higher order phylogroups. The order Bacteroidales showed an overrepresentation (p = 0.05), while the family Lachnospiraceae showed an underrepresentation (p = 0.02) of OTU's associated with depression. At low taxonomic levels, there was one clade consisting of five OTU's within the genus Oscillibacter, and one clade within Alistipes (consisting of four OTU's) that showed a significant association with depression (p = 0.03 and 0.01, respectively). Conclusions & Inferences The Oscillibacter type strain has valeric acid as its main metabolic end product, a homolog of neurotransmitter GABA, while Alistipes has previously been shown to be associated with induced stress in mice. In conclusion, the taxonomic correlations detected here may therefore correspond to mechanistic models.

The current leading view is that functionality and not phylotype is the most important determinant for the services provided by the gut microbiota. Here we present an alternative opinion, advocating the importance of phylotype in addition to function. We believe the literature is misled by technical artifacts in defining operational taxonomic units (OTUs), which are binned groups of bacteria based on sequence homology. Furthermore, the current metagenomic approaches where the total DNA in a sample is mixed prior to sequencing and subsequently resolved by a bioinformatics approach, are highly error prone with respect to both functional and phylotype assignments. We argue that the directions of the OTU and metagenome errors are such that stable phylotypes are overlooked, while functional stability is overestimated. Taking these errors into account, we propose that phylotype represents an interface for functionality, and is for this reason an important determinant for the services provided by the gut microbiota to the host.

Numerous studies have attempted to describe specific microbiota deviations that may precede atopic sensitization and atopic disease in childhood. This has given rise to a hypothesis suggesting that a reduced intestinal microbial diversity in infancy increases the risk of allergic manifestations. This review intends to sum up the main findings and discuss relevant exposures that regulate intestinal microbial diversity.Taken together the three studies in this review lend support to the diversity hypothesis, but reported differences related to atopic sensitization and clinical expression are discussed. A summary on analytic methods and functional aspect of the microbiota in allergic disease is presented to ameliorate a presentation of recent articles on environmental and host-factors regulating microbiota composition and diversity.The current evidence indicates that intestinal microbiota diversity can be associated with allergic diseases, but the exact mechanisms and interactions contributing to this effect are far from understood and need further investigation.

The knowledge about correlation patterns between the fecal microbiota and inflammatory bowel diseases (IBD)—comprising the two subforms Crohn's disease (CD) and ulcerative colitis (UC)—for newly diagnosed untreated children is limited. To address this knowledge gap, a selection of faecal specimens (CD,n=27and UC,n=16) and non-IBD controls (n=30) children (age < 18 years) was analysed utilising bacterial small subunit (SSU) rRNA. We found, surprising age dependence for the fecal microbiota correlating to IBD. The most pronounced patterns were thatE. coliwas positively (R2=0.16,P=0.05) and Bacteroidetes, negatively (R2=0.15,P=0.05) correlated to age for CD patients. For UC, we found an apparent opposite age-related disease correlation for bothBacteroidesandEscherichia. In addition, there was an overrepresentation ofHaemophilusfor the UC children. From our, results we propose a model where the aetiology of IBD is related to an on-going immunological development in children requiring different age-dependent bacterial stimuli. The impact of our findings could be a better age stratification for understanding and treating IBD in children.