Towards a unified medical microbiome ecology of the OMU for metagenomes and the OTU for microbes.

BACKGROUND: Metagenomic sequencing technologies offered unprecedented opportunities and also challenges to microbiology and microbial ecology particularly. The technology has revolutionized the studies of microbes and enabled the high-profile human microbiome and earth microbiome projects. The terminology-change from microbes to microbiomes signals that our capability to count and classify microbes (microbiomes) has achieved the same or similar level as we can for the biomes (macrobiomes) of plants and animals (macrobes). While the traditional investigations of macrobiomes have usually been conducted through naturalists' (Linnaeus & Darwin) naked eyes, and aerial and satellite images (remote-sensing), the large-scale investigations of microbiomes have been made possible by DNA-sequencing-based metagenomic technologies. Two major types of metagenomic sequencing technologies-amplicon sequencing and whole-genome (shotgun sequencing)-respectively generate two contrastingly different categories of metagenomic reads (data)-OTU (operational taxonomic unit) tables representing microorganisms and OMU (operational metagenomic unit), a new term coined in this article to represent various cluster units of metagenomic genes. RESULTS: The ecological science of microbiomes based on the OTU representing microbes has been unified with the classic ecology of macrobes (macrobiomes), but the unification based on OMU representing metagenomes has been rather limited. In a previous series of studies, we have demonstrated the applications of several classic ecological theories (diversity, composition, heterogeneity, and biogeography) to the studies of metagenomes. Here I push the envelope for the unification of OTU and OMU again by demonstrating the applications of metacommunity assembly and ecological networks to the metagenomes of human gut microbiomes. Specifically, the neutral theory of biodiversity (Sloan's near neutral model), Ning et al.stochasticity framework, core-periphery network, high-salience skeleton network, special trio-motif, and positive-to-negative ratio are applied to analyze the OMU tables from whole-genome sequencing technologies, and demonstrated with seven human gut metagenome datasets from the human microbiome project. CONCLUSIONS: All of the ecological theories demonstrated previously and in this article, including diversity, composition, heterogeneity, stochasticity, and complex network analyses, are equally applicable to OMU metagenomic analyses, just as to OTU analyses. Consequently, I strongly advocate the unification of OTU/OMU (microbiomes) with classic ecology of plants and animals (macrobiomes) in the context of medical ecology.

A culture-independent approach, supervised machine learning, and the characterization of the microbial community composition of coastal areas across the Bay of Bengal and the Arabian Sea.

BACKGROUND: Coastal areas are subject to various anthropogenic and natural influences. In this study, we investigated and compared the characteristics of two coastal regions, Andhra Pradesh (AP) and Goa (GA), focusing on pollution, anthropogenic activities, and recreational impacts. We explored three main factors influencing the differences between these coastlines: The Bay of Bengal's shallower depth and lower salinity; upwelling phenomena due to the thermocline in the Arabian Sea; and high tides that can cause strong currents that transport pollutants and debris. RESULTS: The microbial diversity in GA was significantly higher than that in AP, which might be attributed to differences in temperature, soil type, and vegetation cover. 16S rRNA amplicon sequencing and bioinformatics analysis indicated the presence of diverse microbial phyla, including candidate phyla radiation (CPR). Statistical analysis, random forest regression, and supervised machine learning models classification confirm the diversity of the microbiome accurately. Furthermore, we have identified 450 cultures of heterotrophic, biotechnologically important bacteria. Some strains were identified as novel taxa based on 16S rRNA gene sequencing, showing promising potential for further study. CONCLUSION: Thus, our study provides valuable insights into the microbial diversity and pollution levels of coastal areas in AP and GA. These findings contribute to a better understanding of the impact of anthropogenic activities and climate variations on biology of coastal ecosystems and biodiversity.

The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves.

Coastal areas host a major part of marine biodiversity but are seriously threatened by ever-increasing human pressures. Transforming natural coastlines into urban seascapes through habitat artificialization may result in loss of biodiversity and key ecosystem functions. Yet, the extent to which seaports differ from nearby natural habitats and marine reserves across the whole Tree of Life is still unknown. This study aimed to assess the level of α and ß-diversity between seaports and reserves, and whether these biodiversity patterns are conserved across taxa and evolutionary lineages. For that, we used environmental DNA (eDNA) metabarcoding to survey six seaports on the French Mediterranean coast and four strictly no-take marine reserves nearby. By targeting four different groups-prokaryotes, eukaryotes, metazoans and fish-with appropriate markers, we provide a holistic view of biodiversity on contrasted habitats. In the absence of comprehensive reference databases, we used bioinformatic pipelines to gather similar sequences into molecular operational taxonomic units (MOTUs). In contrast to our expectations, we obtained no difference in MOTU richness (α-diversity) between habitats except for prokaryotes and threatened fishes with higher diversity in reserves than in seaports. However, we observed a marked dissimilarity (ß-diversity) between seaports and reserves for all taxa. Surprisingly, this biodiversity signature of seaports was preserved across the Tree of Life, up to the order. This result reveals that seaports and nearby marine reserves share few taxa and evolutionary lineages along urbanized coasts and suggests major differences in terms of ecosystem functioning between both habitats.

Phylogenetic diversity only weakly mitigates climate-change-driven biodiversity loss in insect communities.

To help address the underrepresentation of arthropods and Asian biodiversity from climate-change assessments, we carried out year-long, weekly sampling campaigns with Malaise traps at different elevations and latitudes in Gaoligongshan National Park in southwestern China. From these 623 samples, we barcoded 10,524 beetles and compared scenarios of climate-change-induced biodiversity loss, by designating seasonal, elevational, and latitudinal subsets of beetles as communities that plausibly could go extinct as a group, which we call "loss sets". The availability of a published mitochondrial-genome-based phylogeny of the Coleoptera allowed us to compare the loss of species diversity with and without accounting for phylogenetic relatedness. We hypothesised that phylogenetic relatedness would mitigate extinction, since the extinction of any loss set would result in the disappearance of all its species but only part of its evolutionary history, which is still extant in the remaining loss sets. We found different patterns of community clustering by season and latitude, depending on whether phylogenetic information was incorporated. However, accounting for phylogeny only slightly mitigated the amount of biodiversity loss under climate change scenarios, against our expectations: there is no phylogenetic "escape clause" for biodiversity conservation. We achieve the same results whether phylogenetic information was derived from the mitogenome phylogeny or from a de novo barcode-gene tree. We encourage interested researchers to use this data set to study lineage-specific community assembly patterns in conjunction with life-history traits and environmental covariates.

Investigating the Human Intestinal DNA Virome and Predicting Disease-Associated Virus-Host Interactions in Severe Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).

Understanding how the human virome, and which of its constituents, contributes to health or disease states is reliant on obtaining comprehensive virome profiles. By combining DNA viromes from isolated virus-like particles (VLPs) and whole metagenomes from the same faecal sample of a small cohort of healthy individuals and patients with severe myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), we have obtained a more inclusive profile of the human intestinal DNA virome. Key features are the identification of a core virome comprising tailed phages of the class Caudoviricetes, and a greater diversity of DNA viruses including extracellular phages and integrated prophages. Using an in silico approach, we predicted interactions between members of the Anaerotruncus genus and unique viruses present in ME/CFS microbiomes. This study therefore provides a framework and rationale for studies of larger cohorts of patients to further investigate disease-associated interactions between the intestinal virome and the bacteriome.

Sequence clustering in bioinformatics: an empirical study.

Sequence clustering is a basic bioinformatics task that is attracting renewed attention with the development of metagenomics and microbiomics. The latest sequencing techniques have decreased costs and as a result, massive amounts of DNA/RNA sequences are being produced. The challenge is to cluster the sequence data using stable, quick and accurate methods. For microbiome sequencing data, 16S ribosomal RNA operational taxonomic units are typically used. However, there is often a gap between algorithm developers and bioinformatics users. Different software tools can produce diverse results and users can find them difficult to analyze. Understanding the different clustering mechanisms is crucial to understanding the results that they produce. In this review, we selected several popular clustering tools, briefly explained the key computing principles, analyzed their characters and compared them using two independent benchmark datasets. Our aim is to assist bioinformatics users in employing suitable clustering tools effectively to analyze big sequencing data. Related data, codes and software tools were accessible at the link http://lab.malab.cn/∼lg/clustering/.

Metagenomics of two gnotobiotically grown aromatic rice cultivars reveals genotype-dependent and tissue-specific colonization of endophytic bacterial communities attributing multiple plant growth promoting traits.

Exploration of community structures, habitations, and potential plant growth promoting (PGP) attributes of endophytic bacteria through next generation sequencing (NGS) is a prerequisite to culturing PGP endophytic bacteria for their application in sustainable agriculture. The present study unravels the taxonomic abundance and diversity of endophytic bacteria inhabiting in vitro grown root, shoot and callus tissues of two aromatic rice cultivars through 16S rRNA gene-based Illumina NGS. Wide variability in the number of bacterial operational taxonomic units (OTUs) and genera was observed between the two samples of the root (55, 14 vs. 310, 76) and shoot (26, 12 vs. 276, 73) but not between the two callus samples (251, 61 vs. 259, 51), indicating tissue-specific and genotype-dependent bacterial community distribution in rice plant, even under similar gnotobiotic growth conditions. Sizes of core bacteriomes of the selected two rice genotypes varied from 1 to 15 genera, with Sphingomonas being the only genus detected in all six samples. Functional annotation, based upon the abundance of bacterial OTUs, revealed the presence of several PGP trait-related genes having variable relative abundance in tissue-specific and genotype-dependent manners. In silico study also documented a higher abundance of certain genes in the same biochemical pathway, such as nitrogen fixation, phosphate solubilization and indole acetic acid production; implying their crucial roles in the biosynthesis of metabolites leading to PGP. New insights on utilizing callus cultures for isolation of PGP endophytes aiming to improve rice crop productivity are presented, owing to constancy in bacterial OTUs and genera in callus tissues of both the rice genotypes.

Accumulation curves of environmental DNA sequences predict coastal fish diversity in the coral triangle.

Environmental DNA (eDNA) has the potential to provide more comprehensive biodiversity assessments, particularly for vertebrates in species-rich regions. However, this method requires the completeness of a reference database (i.e. a list of DNA sequences attached to each species), which is not currently achieved for many taxa and ecosystems. As an alternative, a range of operational taxonomic units (OTUs) can be extracted from eDNA metabarcoding. However, the extent to which the diversity of OTUs provided by a limited eDNA sampling effort can predict regional species diversity is unknown. Here, by modelling OTU accumulation curves of eDNA seawater samples across the Coral Triangle, we obtained an asymptote reaching 1531 fish OTUs, while 1611 fish species are recorded in the region. We also accurately predict (R² = 0.92) the distribution of species richness among fish families from OTU-based asymptotes. Thus, the multi-model framework of OTU accumulation curves extends the use of eDNA metabarcoding in ecology, biogeography and conservation.

Freshwater mussels (Bivalvia: Unionidae) from the rising sun (Far East Asia): phylogeny, systematics, and distribution.

Freshwater mussels (Bivalvia: Unionidae) is a diverse family with around 700 species being widespread in the Northern Hemisphere and Africa. These animals fulfill key ecological functions and provide important services to humans. Unfortunately, populations have declined dramatically over the last century, rendering Unionidae one of the world's most imperiled taxonomic groups. In Far East Asia (comprising Japan, Korea, and Eastern Russia), conservation actions have been hindered by a lack of basic information on the number, identity, distribution and phylogenetic relationships of species. Available knowledge is restricted to studies on national and sub-national levels. The present study aims to resolve the diversity, biogeography and evolutionary relationships of the Far East Asian Unionidae in a globally comprehensive phylogenetic and systematic context. We reassessed the systematics of all Unionidae species in the region, including newly collected specimens from across Japan, South Korea, and Russia, based on molecular (including molecular species delineation and a COI + 28S phylogeny) and comparative morphological analyses. Biogeographical patterns were then assessed based on available species distribution data from the authors and previous reference works. We revealed that Unionidae species richness in Far East Asia is 30% higher than previously assumed, counting 43 species (41 native + 2 alien) within two Unionidae subfamilies, the Unioninae (32 + 1) and Gonideinae (9 + 1). Four of these species are new to science, i.e. Beringiana gosannensissp. nov., Beringiana fukuharaisp. nov., Buldowskia kamiyaisp. nov., and Koreosolenaia sitgyensisgen. & sp. nov. We also propose a replacement name for Nodularia sinulata, i.e. Nodularia breviconchanom. nov. and describe a new tribe (Middendorffinaiini tribe nov.) within the Unioninae subfamily. Biogeographical patterns indicate that this fauna is related to that from China south to Vietnam until the Mekong River basin. The Japanese islands of Honshu, Shikoku, Kyushu, Hokkaido, and the Korean Peninsula were identified as areas of particularly high conservation value, owing to high rates of endemism, diversity and habitat loss. The genetically unique species within the genera Amuranodonta, Obovalis, Koreosolenaiagen. nov., and Middendorffinaia are of high conservation concern.

Network Analysis of Gut Microbiome and Metabolome to Discover Microbiota-Linked Biomarkers in Patients Affected by Non-Small Cell Lung Cancer.

Several studies in recent times have linked gut microbiome (GM) diversity to the pathogenesis of cancer and its role in disease progression through immune response, inflammation and metabolism modulation. This study focused on the use of network analysis and weighted gene co-expression network analysis (WGCNA) to identify the biological interaction between the gut ecosystem and its metabolites that could impact the immunotherapy response in non-small cell lung cancer (NSCLC) patients undergoing second-line treatment with anti-PD1. Metabolomic data were merged with operational taxonomic units (OTUs) from 16S RNA-targeted metagenomics and classified by chemometric models. The traits considered for the analyses were: (i) condition: disease or control (CTRLs), and (ii) treatment: responder (R) or non-responder (NR). Network analysis indicated that indole and its derivatives, aldehydes and alcohols could play a signaling role in GM functionality. WGCNA generated, instead, strong correlations between short-chain fatty acids (SCFAs) and a healthy GM. Furthermore, commensal bacteria such as Akkermansia muciniphila, Rikenellaceae, Bacteroides, Peptostreptococcaceae, Mogibacteriaceae and Clostridiaceae were found to be more abundant in CTRLs than in NSCLC patients. Our preliminary study demonstrates that the discovery of microbiota-linked biomarkers could provide an indication on the road towards personalized management of NSCLC patients.

Bacterial metagenome analysis of Mytilus galloprovincialis collected from Istanbul and Izmir coastal stations of Turkey.

Mytilus galloprovincialis is a marine mollusk belonging to the Bivalvia class. It has been distributed largely in Turkish shores and worldwide aquatic environments. Besides being known as an environmental pollution indicator, it is highly consumed as a food and has a high economic value. Due to their nutritional mechanisms by filtering water, they are affected by pollution in seawater and mussels can host-microbial diversity of environmental origin as well as pathogenic bacteria. Therefore, in this study, bacterial species found in Mediterranean mussels collected from the coastal stations of Istanbul [Rumeli Kavagi (RK), Kucukcekmece (KC)], and Izmir [(Foca (MF), Urla (MU)] were investigated and compared with microbiological and metagenomic analyses. According to microbiological analysis results, 34 mussel-associated Enterobacteriaceae and Vibrionaceae family members were identified. As a result of the culture-independent metagenomic analysis, taxonomic groups for each station were identified and compared based on Operational Taxonomic Unit data. For all stations, the most abundant bacterial genera were the unclassified bacterial genera. The total number of mussel-related total richness identified in all groups was 4889 (RK = 1605; KC = 1930; MF = 1508; and MU = 1125). According to the metagenomic data obtained in this study, different relative amounts of Lachnospiraceae and Bacteroidetes taxa groups were reported for all stations. The pathogenic bacterial genera identified by metagenomic analyses which may be significant for the public health are Arcobacter, Clostridium, Aeromonas, Vibrio, Escherichia_Shigella, Klebsiella, Campylobacter, Helicobacter, Pseudomonas, Morganella, Serratia, Corynebacterium, Enterococcus, Staphylococcus, Yersinia, Mycoplasma, Brucellaceae_unclassified, Pantoea, and Proteus.

Relative reduction of biological and phylogenetic diversity of the oral microbiota of diabetes and pre-diabetes patients.

BACKGROUND: A reciprocal relationship between oral health and systemic disease, such as type 2 diabetes, has been suggested, whereby a systemic disease is a predisposing factor for oral infection. If the infection occurs, it in turn aggravates the progression of the systemic disease. According to several studies, certain constituents of the oral microbiota are linked to diabetes, metabolic syndrome, and obesity. In the current study, we aimed to compare the microbial diversity and population structure of the oral microbiota of normoglycemic, impaired glucose tolerance (IGT), and diabetes patients. METHODOLOGY: The study followed a case-control design, with 15 type 2 diabetes patients, 10 IGT subjects, and 19 control subjects. All subjects underwent assessment of periodontitis and oral health. Saliva samples were collected, and DNA was isolated from these samples. Hypervariable regions of the 16Sr RNA gene were amplified and sequenced, and the generated sequences underwent bioinformatics analysis. Statistical analysis and diversity index calculations were made using the statistical software R, vegan R-package, and Past3.20 software. RESULTS: Overall, 551 operational taxonomic units (OTUs) were identified. Based on OTU analysis, a clear reduction of the number of species was observed in both IGT (412) and diabetes groups (372) compared with that in the normoglycemic group (502). This was associated with a similar pattern of reduction of biological diversity among the three groups. The phylogenetic diversity (PD-SBL) value in the normoglycemic group was higher than that in the diabetes group. The diabetes group exhibited the highest evenness value and the highest microbiota bacterial pathogenic content. CONCLUSION: A clear reduction of the biological and phylogenetic diversity was apparent in the diabetes and pre-diabetes oral microbiota in comparison with that in the normoglycemic oral microbiota. However, this was associated with an increase in the pathogenic content of the hyperglycemic microbiota. The results of this study may aid to better understanding of the directionality of the mysterious reciprocal relationship.

Oat bran, but not its isolated bioactive ß-glucans or polyphenols, have a bifidogenic effect in an in vitro fermentation model of the gut microbiota.

Wholegrain oats are known to modulate the human gut microbiota and have prebiotic properties (increase the growth of some health-promoting bacterial genera within the colon). Research to date mainly attributes these effects to the fibre content; however, oat is also a rich dietary source of polyphenols, which may contribute to the positive modulation of gut microbiota. In vitro anaerobic batch-culture experiments were performed over 24 h to evaluate the impact of two different doses (1 and 3 % (w/v)) of oat bran, matched concentrations of ß-glucan extract or polyphenol mix, on the human faecal microbiota composition using 16S RNA gene sequencing and SCFA analysis. Supplementation with oats increased the abundance of Proteobacteria (P <0·01) at 10 h, Bacteroidetes (P <0·05) at 24 h and concentrations of acetic and propionic acid increased at 10 and 24 h compared with the NC. Fermentation of the 1 % (w/v) oat bran resulted in significant increase in SCFA production at 24 h (86 (sd 27) v. 28 (sd 5) mm; P <0·05) and a bifidogenic effect, increasing the relative abundance of Bifidobacterium unassigned at 10 h and Bifidobacterium adolescentis (P <0·05) at 10 and 24 h compared with NC. Considering the ß-glucan treatment induced an increase in the phylum Bacteroidetes at 24 h, it explains the Bacteriodetes effects of oats as a food matrix. The polyphenol mix induced an increase in Enterobacteriaceae family at 24 h. In conclusion, in this study, we found that oats increased bifidobacteria, acetic acid and propionic acid, and this is mediated by the synergy of all oat compounds within the complex food matrix, rather than its main bioactive ß-glucan or polyphenols. Thus, oats as a whole food led to the greatest impact on the microbiota.

Computational molecular species delimitation and taxonomic revision of the gecko genus Ebenavia Boettger, 1878.

Cryptic species have been detected in many groups of organisms and must be assumed to make up a significant portion of global biodiversity. We study geckos of the Ebenavia inunguis complex from Madagascar and surrounding islands and use species delimitation algorithms (GMYC, BOLD, BPP), COI barcode divergence, diagnostic codon indels in the nuclear marker PRLR, diagnostic categorical morphological characters, and significant differences in continuous morphological characters for its taxonomic revision. BPP yielded ≥ 10 operational taxonomic units, whereas GMYC (≥ 27) and BOLD (26) suggested substantial oversplitting. In consequnce, we resurrect Ebenavia boettgeri Boulenger 1885 and describe Ebenavia tuelinae sp. nov., Ebenavia safari sp. nov., and Ebenavia robusta sp. nov., increasing the number of recognised species in Ebenavia from two to six. Further lineages of Ebenavia retrieved by BPP may warrant species or subspecies status, but further taxonomic conclusions are postponed until more data become available. Finally, we present an identification key to the genus Ebenavia, provide an updated distribution map, and discuss the diagnostic values of computational species delimitation as well as morphological and molecular diagnostic characters.

Numerical analyses of intestinal microbiota by data mining.

The human intestinal microbiota has a close relationship with health control and causes of diseases, and a vast number of scientific papers on this topic have been published recently. Some progress has been made in identifying the causes or species of related microbiota, and successful results of data mining are reviewed here. Humans who are targets of a disease have their own individual characteristics, including various types of noise because of their individual life style and history. The quantitatively dominant bacterial species are not always deeply connected with a target disease. Instead of conventional simple comparisons of the statistical record, here the Gini-coefficient (i.e., evaluation of the uniformity of a group) was applied to minimize the effects of various types of noise in the data. A series of results were reviewed comparatively for normal daily life, disease and technical aspects of data mining. Some representative cases (i.e., heavy smokers, Crohn's disease, coronary artery disease and prediction accuracy of diagnosis) are discussed in detail. In conclusion, data mining is useful for general diagnostic applications with reasonable cost and reproducibility.

Evaluating the accuracy of amplicon-based microbiome computational pipelines on simulated human gut microbial communities.

BACKGROUND: Microbiome studies commonly use 16S rRNA gene amplicon sequencing to characterize microbial communities. Errors introduced at multiple steps in this process can affect the interpretation of the data. Here we evaluate the accuracy of operational taxonomic unit (OTU) generation, taxonomic classification, alpha- and beta-diversity measures for different settings in QIIME, MOTHUR and a pplacer-based classification pipeline, using a novel software package: DECARD. RESULTS: In-silico we generated 100 synthetic bacterial communities approximating human stool microbiomes to be used as a gold-standard for evaluating the colligative performance of microbiome analysis software. Our synthetic data closely matched the composition and complexity of actual healthy human stool microbiomes. Genus-level taxonomic classification was correctly done for only 50.4-74.8% of the source organisms. Miscall rates varied from 11.9 to 23.5%. Species-level classification was less successful, (6.9-18.9% correct); miscall rates were comparable to those of genus-level targets (12.5-26.2%). The degree of miscall varied by clade of organism, pipeline and specific settings used. OTU generation accuracy varied by strategy (closed, de novo or subsampling), reference database, algorithm and software implementation. Shannon diversity estimation accuracy correlated generally with OTU-generation accuracy. Beta-diversity estimates with Double Principle Coordinate Analysis (DPCoA) were more robust against errors introduced in processing than Weighted UniFrac. The settings suggested in the tutorials were among the worst performing in all outcomes tested. CONCLUSIONS: Even when using the same classification pipeline, the specific OTU-generation strategy, reference database and downstream analysis methods selection can have a dramatic effect on the accuracy of taxonomic classification, and alpha- and beta-diversity estimation. Even minor changes in settings adversely affected the accuracy of the results, bringing them far from the best-observed result. Thus, specific details of how a pipeline is used (including OTU generation strategy, reference sets, clustering algorithm and specific software implementation) should be specified in the methods section of all microbiome studies. Researchers should evaluate their chosen pipeline and settings to confirm it can adequately answer the research question rather than assuming the tutorial or standard-operating-procedure settings will be adequate or optimal.

Probiotic yogurt and acidified milk similarly reduce postprandial inflammation and both alter the gut microbiota of healthy, young men.

Probiotic yogurt and milk supplemented with probiotics have been investigated for their role in 'low-grade' inflammation but evidence for their efficacy is inconclusive. This study explores the impact of probiotic yogurt on metabolic and inflammatory biomarkers, with a parallel study of gut microbiota dynamics. The randomised cross-over study was conducted in fourteen healthy, young men to test probiotic yogurt compared with milk acidified with 2 % d-(+)-glucono-δ-lactone during a 2-week intervention (400 g/d). Fasting assessments, a high-fat meal test (HFM) and microbiota analyses were used to assess the intervention effects. Baseline assessments for the HFM were carried out after a run-in during which normal milk was provided. No significant differences in the inflammatory response to the HFM were observed after probiotic yogurt compared with acidified milk intake; however, both products were associated with significant reductions in the inflammatory response to the HFM compared with the baseline tests (assessed by IL6, TNFα and chemokine ligand 5) (P<0·001). These observations were accompanied by significant changes in microbiota taxa, including decreased abundance of Bilophila wadsworthia after acidified milk (log 2-fold-change (FC)=-1·5, P adj=0·05) and probiotic yogurt intake (FC=-1·3, P adj=0·03), increased abundance of Bifidobacterium species after acidified milk intake (FC=1·4, P adj=0·04) and detection of Lactobacillus delbrueckii spp. bulgaricus (FC=7·0, P adj<0·01) and Streptococcus salivarius spp. thermophilus (FC=6·0, P adj<0·01) after probiotic yogurt intake. Probiotic yogurt and acidified milk similarly reduce postprandial inflammation that is associated with a HFM while inducing distinct changes in the gut microbiota of healthy men. These observations could be relevant for dietary treatments that target 'low-grade' inflammation.

Polymannuronic acid ameliorated obesity and inflammation associated with a high-fat and high-sucrose diet by modulating the gut microbiome in a murine model.

Polymannuronic acid (PM), one of numerous alginates isolated from brown seaweeds, is known to possess antioxidant activities. In this study, we examined its potential role in reducing body weight gain and attenuating inflammation induced by a high-fat and high-sucrose diet (HFD) as well as its effect on modulating the gut microbiome in mice. A 30-d PM treatment significantly reduced the diet-induced body weight gain and blood TAG levels (P2·0). PM also had a profound impact on the microbial composition in the gut microbiome and resulted in a distinct microbiome structure. For example, PM significantly increased the abundance of a probiotic bacterium, Lactobacillus reuteri (log10 LDA score>2·0). Together, our results suggest that PM may exert its immunoregulatory effects by enhancing proliferation of several species with probiotic activities while repressing the abundance of the microbial taxa that harbor potential pathogens. Our findings should facilitate mechanistic studies on PM as a potential bioactive compound to alleviate obesity and the metabolic syndrome.

Fungal DNA barcoding.

Fungi are ubiquitous in both natural and human-made environments. They play important roles in the health of plants, animals, and humans, and in broad ecosystem functions. Thus, having an efficient species-level identification system could significantly enhance our ability to treat fungal diseases and to monitor the spatial and temporal patterns of fungal distributions and migrations. DNA barcoding is a potent approach for rapid identification of fungal specimens, generating novel species hypothesis, and guiding biodiversity and ecological studies. In this mini-review, I briefly summarize (i) the history of DNA sequence-based fungal identification; (ii) the emergence of the ITS region as the consensus primary fungal barcode; (iii) the use of the ITS barcodes to address a variety of issues on fungal diversity from local to global scales, including generating a large number of species hypothesis; and (iv) the problems with the ITS barcode region and the approaches to overcome these problems. Similar to DNA barcoding research on plants and animals, significant progress has been achieved over the last few years in terms of both the questions being addressed and the foundations being laid for future research endeavors. However, significant challenges remain. I suggest three broad areas of research to enhance the usefulness of fungal DNA barcoding to meet the current and future challenges: (i) develop a common set of primers and technologies that allow the amplification and sequencing of all fungi at both the primary and secondary barcode loci; (ii) compile a centralized reference database that includes all recognized fungal species as well as species hypothesis, and allows regular updates from the research community; and (iii) establish a consensus set of new species recognition criteria based on barcode DNA sequences that can be applied across the fungal kingdom.

Minimal short-term effect of dietary 2'-fucosyllactose on bacterial colonisation, intestinal function and necrotising enterocolitis in preterm pigs.

Human milk decreases the risk of necrotising enterocolitis (NEC), a severe gastrointestinal disease that occurs in 5-10 % of preterm infants. The prebiotic and immune-modulatory effects of milk oligosaccharides may contribute to this protection. Preterm pigs were used to test whether infant formula enriched with α1,2-fucosyllactose (2'-FL, the most abundant oligosaccharide in human milk) would benefit gut microbial colonisation and NEC resistance after preterm birth. Caesarean-delivered preterm pigs were fed formula (Controls, n 17) or formula with 5 g/l 2'-FL (2'-FL, n 16) for 5 d; eight 2'-FL pigs (50 %) and twelve Controls (71 %) developed NEC, with no difference in lesion scores (P=0·35); 2'-FL pigs tended to have less anaerobic bacteria in caecal contents (P=0·22), but no difference in gut microbiota between groups were observed by fluorescence in situ hybridisation and 454 pyrosequencing. Abundant α1,2-fucose was detected in the intestine with no difference between groups, and intestinal structure (villus height, permeability) and digestive function (hexose absorption, brush border enzyme activities) were not affected by 2'-FL. Formula enrichment with 2'-FL does not affect gut microbiology, digestive function or NEC sensitivity in pigs within the first few days after preterm birth. Milk 2'-FL may not be critical in the immediate postnatal period of preterm neonates when gut colonisation and intestinal immunity are still immature.