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Background Microbiome studies often involve sequencing a marker gene to identify the microorganisms in samples of interest. Sequence classification is a critical component of this process, whereby sequences are assigned to a reference taxonomy containing known sequence representatives of many microbial groups. Previous studies have shown that existing classification programs often assign sequences to reference groups even if they belong to novel taxonomic groups that are absent from the reference taxonomy. This high rate of “over classification” is particularly detrimental in microbiome studies because reference taxonomies are far from comprehensive. Results Here, we introduce IDTAXA, a novel approach to taxonomic classification that employs principles from machine learning to reduce over classification errors. Using multiple reference taxonomies, we demonstrate that IDTAXA has higher accuracy than popular classifiers such as BLAST, MAPSeq, QIIME, SINTAX, SPINGO, and the RDP Classifier. Similarly, IDTAXA yields far fewer over classifications on Illumina mock microbial community data when the expected taxa are absent from the training set. Furthermore, IDTAXA offers many practical advantages over other classifiers, such as maintaining low error rates across varying input sequence lengths and withholding classifications from input sequences composed of random nucleotides or repeats. Conclusions IDTAXA’s classifications may lead to different conclusions in microbiome studies because of the substantially reduced number of taxa that are incorrectly identified through over classification. Although misclassification error is relatively minor, we believe that many remaining misclassifications are likely caused by errors in the reference taxonomy. We describe how IDTAXA is able to identify many putative mislabeling errors in reference taxonomies, enabling training sets to be automatically corrected by eliminating spurious sequences. IDTAXA is part of the DECIPHER package for the R programming language, available through the Bioconductor repository or accessible online ( http://DECIPHER.codes ).

Background Precision therapy for lung cancer requires comprehensive genomic analyses. Specific effects of targeted therapies have been reported in Asia populations, including Taiwanese, but genomic studies have rarely been performed in these populations. Method We enrolled 72 patients with non-small cell lung cancer, of whom 61 had adenocarcinoma, 10 had squamous cell carcinoma, and 1 had combined adenocarcinoma and squamous cell carcinoma. Whole-exome or targeted gene sequencing was performed. To identify trunk mutations, we performed whole-exome sequencing in two tumor regions in four patients. Results Nineteen known driver mutations in EGFR , PIK3CA , KRAS , CTNNB1 , and MET were identified in 34 of the 72 tumors evaluated (47.22%). A comparison with the Cancer Genome Atlas dataset showed that EGFR was mutated at a much higher frequency in our cohort than in Caucasians, whereas KRAS and TP53 mutations were found in only 5.56% and 25% of our Taiwanese patients, respectively. We also identified new mutations in ARID1A , ARID2 , CDK12 , CHEK2 , GNAS , H3F3A , KDM6A , KMT2C , NOTCH1 , RB1 , RBM10 , RUNX1 , SETD2 , SF3B1 , SMARCA4 , THRAP3 , TP53 , and ZMYM2 . Moreover, all ClinVar pathogenic variants were trunk mutations present in two regions of a tumor. RNA sequencing revealed that the trunk or branch genes were expressed at similar levels among different tumor regions. Conclusions We identified novel variants potentially associated with lung cancer tumorigenesis. The specific mutation pattern in Taiwanese patients with non-small cell lung cancer may influence targeted therapies.

The existence of a placental microbiota is debated. The human placenta has historically been considered sterile and microbial colonization was associated with adverse pregnancy outcomes. Yet, recent DNA sequencing investigations reported a microbiota in typical human term placentas. However, this detected microbiota could represent background DNA or delivery-associated contamination. Using fifteen publicly available 16S rRNA gene datasets, existing data were uniformly re-analyzed with DADA2 to maximize comparability. While Amplicon Sequence Variants (ASVs) identified as Lactobacillus , a typical vaginal bacterium, were highly abundant and prevalent across studies, this prevalence disappeared after applying likely  DNA contaminant removal to placentas from term cesarean deliveries. A six-study sub-analysis targeting the 16S rRNA gene V4 hypervariable region demonstrated that bacterial profiles of placental samples and technical controls share principal bacterial ASVs and that placental samples clustered primarily by study origin and mode of delivery. Contemporary DNA-based evidence does not support the existence of a placental microbiota. Importance Early-gestational microbial influences on human development are unclear. By applying DNA sequencing technologies to placental tissue, bacterial DNA signals were observed, leading some to conclude that a live bacterial placental microbiome exists in typical term pregnancy. However, the low-biomass nature of the proposed microbiome and high sensitivity of current DNA sequencing technologies indicate that the signal may alternatively derive from environmental or delivery-associated bacterial DNA contamination. Here we address these alternatives with a re-analysis of 16S rRNA gene sequencing data from 15 publicly available placental datasets. After identical DADA2 pipeline processing of the raw data, subanalyses were performed to control for mode of delivery and environmental DNA contamination. Both environment and mode of delivery profoundly influenced the bacterial DNA signal from term-delivered placentas. Aside from these contamination-associated signals, consistency was lacking across studies. Thus, placentas delivered at term are unlikely to be the original source of observed bacterial DNA signals.

Abstract We investigated the effects of substrate (cellulose or starch) and different clay contents on the production of microbial extracellular polymeric substances (EPS) and concomitant development of stable soil aggregates. Soils were incubated with different amounts of montmorillonite (+ 0.1%, + 1%, + 10%) both with and without two substrates of contrasting quality (starch and cellulose). Microbial respiration (CO2), biomass carbon (C), EPS-protein, and EPS-polysaccharide were determined over the experimental period. The diversity and compositional shifts of microbial communities (bacteria/archaea) were analysed by sequencing 16S rRNA gene fragments amplified from soil DNA. Soil aggregate size distribution was determined and geometric mean diameter calculated for aggregate formation. Aggregate stabilities were compared among 1–2-mm size fraction. Starch amendment supported a faster increase than cellulose in both respiration and microbial biomass. Microbial community structure and composition differed depending on the C substrate added. However, clay addition had a more pronounced effect on alpha diversity compared to the addition of starch or cellulose. Substrate addition resulted in an increased EPS concentration only if combined with clay addition. At high clay addition, starch resulted in higher EPS concentrations than cellulose. Where additional substrate was not provided, EPS-protein was only weakly correlated with aggregate formation and stability. The relationship became stronger with addition of substrate. Labile organic C thus clearly plays a role in aggregate formation, but increasing clay content was found to enhance aggregate stability and additionally resulted in the development of distinct microbial communities and increased EPS production.

Background Accurate estimation of the microbial load is crucial for diagnosing infections and guiding treatment decisions. While traditional culture methods are informative, they are limited by their inability to grow all organisms. Next-generation sequencing offers a more comprehensive alternative for identifying and quantifying microbial communities. This study explored the application of full-length 16S rRNA gene sequencing for bacterial quantification by incorporating internal controls. Methods We optimized full-length16S rRNA gene sequencing using nanopore technology, on commercially available mock community standards. We varied DNA input, PCR cycles, and spike-in proportions. The method was then validated using human samples from the stool, saliva, nose, and skin, and a spike-in control for quantification. Community profiling was done with Emu. Results Emu performed well at providing genus and species-level resolution. The use of spike-in provided robust quantification across varying DNA inputs and sample origin. However, challenges remained in detecting low-abundance taxa and differentiating closely related species. Human samples with varying microbial loads showed high concordance between sequencing estimates and culture methods. Conclusion These findings demonstrate that full-length 16S rRNA gene sequencing, combined with spike-ins, offers a reliable and scalable approach for microbial quantification. The method’s performance across diverse human microbiomes supports its potential use in clinical diagnostics where bacterial identification and load estimation are critical. However, further refinement is needed to address limitations in detecting low-abundance and closely related species.

Dysbiotic gut microbiota have been implicated in human disease. Diet-based therapeutic strategies have been used to manipulate the gut microbiota towards a more favourable profile. However, it has been demonstrated that large inter-individual variability exists in gut microbiota response to a dietary intervention. The primary objective of this study was to investigate whether habitually low dietary fibre (LDF) v. high dietary fibre (HDF) intakes influence gut microbiota response to an inulin-type fructan prebiotic. In this randomised, double-blind, placebo-controlled, cross-over study, thirty-four healthy participants were classified as LDF or HDF consumers. Gut microbiota composition (16S rRNA bacterial gene sequencing) and SCFA concentrations were assessed following 3 weeks of daily prebiotic supplementation (Orafti® Synergy 1; 16 g/d) or placebo (Glucidex® 29 Premium; 16 g/d), as well as after 3 weeks of the alternative intervention, following a 3-week washout period. In the LDF group, the prebiotic intervention led to an increase in Bifidobacterium (P=0·001). In the HDF group, the prebiotic intervention led to an increase in Bifidobacterium (P<0·001) and Faecalibacterium (P=0·010) and decreases in Coprococcus (P=0·010), Dorea (P=0·043) and Ruminococcus (Lachnospiraceae family) (P=0·032). This study demonstrates that those with HDF intakes have a greater gut microbiota response and are therefore more likely to benefit from an inulin-type fructan prebiotic than those with LDF intakes. Future studies aiming to modulate the gut microbiota and improve host health, using an inulin-type fructan prebiotic, should take habitual dietary fibre intake into account.

Background DNA extraction is an important factor influencing the microbiome profile in fecal samples. Considering that the QIAamp DNA Stool Mini Kit, one of the most commonly used DNA extraction kits, is no longer manufactured, this study aimed to investigate whether a new commercially available kit, the QIAamp PowerFecal Pro DNA Kit, yields comparable microbiome profiles with those previously obtained using the QIAamp DNA Stool Mini Kit. Results We extracted DNA from fecal samples of 10 individuals using three protocols (protocol P of the QIAamp PowerFecal Pro DNA Kit, and protocols SB and S of the QIAamp DNA Stool Mini Kit with and without an additional bead-beating step, respectively) in triplicate. Ninety extracted DNA samples were subjected to 16S rRNA gene sequencing. DNA quality measured by 260/280 absorbance ratios was found to be optimal in protocol P. Additionally, the DNA quantity and microbiome diversity obtained using protocol P were significantly higher than those of protocol S, however, did not differ significantly from those of protocol SB. Based on the overall microbiome profiles, variations between protocol P and protocol SB or S were significantly less than between-individual variations. Furthermore, most genera were not differentially abundant in protocol P compared to the other protocols, and the number of differentially abundant genera, as well as the degree of fold-changes were smaller between protocols P and SB than between protocols P and S. Conclusions The QIAamp PowerFecal Pro DNA Kit exhibited microbiome analysis results that were comparable with those of the QIAamp DNA Stool Mini Kit with a bead-beating step. These results will prove useful for researchers investigating the gut microbiome in selecting an alternative protocol to the widely used but discontinued kit.

ABSTRACT Members of the phylum Planctomycetes are common inhabitants of boreal Sphagnum peat bogs and lichen-dominated tundra wetlands. These bacteria colonize both oxic and anoxic peat layers and reach the population size of 107 cells per gram of wet peat. The 16S rRNA gene sequences from planctomycetes comprise 5%–22% of total 16S rRNA gene reads retrieved from peat samples. Most abundant peat-inhabiting planctomycetes affiliate with the families Isosphaeraceae and Gemmataceae, and with as-yet-uncultured Phycisphaera-related group WD2101. The use of metatranscriptomics to assess the functional role of planctomycetes in peatlands suggested the presence of versatile hydrolytic capabilities in these bacteria. This evidence was further confirmed by the analysis of genome-encoded capabilities of isolates from wetlands. Large (up to 12 Mbp) genomes of planctomycetes encode wide repertoires of carbohydrate-active enzymes including many unclassified putative glycoside hydrolases, which suggests the presence of extremely high glycolytic potential in these bacteria. Experimental tests confirmed their ability to grow on xylan, pectin, starch, lichenan, cellulose, chitin and polysaccharides of microbial origin. These results provide an insight into the ecological roles of peat-inhabiting planctomycetes and suggest their participation in degradation of plant-derived polymers, exoskeletons of peat-inhabiting arthropods as well as exopolysaccharides produced by other bacteria. This mini-review summarizes the currently available knowledge on the abundance, phylogenetic diversity, specific adaptations and potential roles of planctomycetes in peatlands.

While pathogens of the eye have been studied for a very long time, the existence of resident microbes on the surface of healthy eyes has gained interest only recently. It appears that commensal microbes are a normal feature of the healthy eye, whose role and properties are currently the subject of extensive research. This review provides an overview of studies that have used 16s rRNA gene sequencing and whole metagenome shotgun sequencing to characterize microbial communities associated with the healthy ocular surface from kingdom to genus level. Bacteria are the primary colonizers of the healthy ocular surface, with three predominant phyla: , and , regardless of the host, environment, and method used. Refining the microbial classification to the genus level reveals a highly variable distribution from one individual and study to another. Factors accounting for this variability are intriguing - it is currently unknown to what extent this is attributable to the individuals and their environment and how much is artifactual. Clearly, it is technically challenging to accurately describe the microorganisms of the ocular surface because their abundance is relatively low, thus, permitting substantial contaminations. More research is needed, including better experimental standards to prevent biases, and the exploration of the ocular surface microbiome's role in a spectrum of healthy to pathological states. Outcomes from such research include the opportunity for therapeutic interventions targeting the microbiome.

This review article on the skin microbiota was written in response to recent advances that transitioned from culture methods to PCR amplification and sequencing of bacterial and fungal genes as a result of the Human Microbiome Project. This transition enables the investigation of the full diversity of microorganisms inhabiting human skin. The skin provides a range of habitats with different microbiota associated with the three major regions of the skin, namely the moist axilla, perineum, and toe webs; oily or sebaceous head, neck, and trunk; and dry forearms and legs. These new culture-independent tools are revealing the diversity of the human skin microbiota in the different locations of the body and with skin depth. These tools should lead to a better understanding of the state of homeostasis between the microbiota and the host and the overall functionality of that microbiota.