Explore the vast range of titles available.

The Antarctic Circumpolar Current (ACC) is the major current in the Southern Ocean, isolating the warm stratified subtropical waters from the more homogeneous cold polar waters. The ACC flows from west to east around Antarctica and generates an overturning circulation by fostering deep-cold water upwelling and the formation of new water masses, thus affecting the Earth’s heat balance and the global distribution of carbon. The ACC is characterized by several water mass boundaries or fronts, known as the Subtropical Front (STF), Subantarctic Front (SAF), Polar Front (PF), and South Antarctic Circumpolar Current Front (SACCF), identified by typical physical and chemical properties. While the physical characteristics of these fronts have been characterized, there is still poor information regarding the microbial diversity of this area. Here we present the surface water bacterioplankton community structure based on 16S rRNA sequencing from 13 stations sampled in 2017 between New Zealand to the Ross Sea crossing the ACC Fronts. Our results show a distinct succession in the dominant bacterial phylotypes present in the different water masses and suggest a strong role of sea surface temperatures and the availability of Carbon and Nitrogen in controlling community composition. This work represents an important baseline for future studies on the response of Southern Ocean epipelagic microbial communities to climate change.

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 ).

The consumption of probiotics is widely encouraged due to reports of their positive effects on human health. In particular, Lacticaseibacillus rhamnosus strain GG (LGG) is an approved probiotic that has been reported to improve health outcomes, especially for gastrointestinal disorders. However, how LGG cooperates with the gut microbiome has not been fully explored. To understand the interaction between LGG and its ability to survive and grow within the gut microbiome, this study introduced LGG into established microbial communities using an in vitro model of the colon. LGG was inoculated into the simulated ascending colon and its persistence in, and transit through the subsequent transverse and descending colon regions was monitored over two weeks. The impact of LGG on the existing bacterial communities was investigated using 16S rRNA sequencing and short-chain fatty acid analysis. LGG was able to engraft and proliferate in the ascending region for at least 10 days but was diminished in the transverse and descending colon regions with little effect on short-chain fatty acid abundance. These data suggest that the health benefits of the probiotic LGG rely on its ability to transiently engraft and modulate the host microbial community.

Although gut microbiome dysbiosis has been associated with inflammatory bowel disease (IBD), the relationship between the oral microbiota and IBD remains poorly understood. This study aimed to identify unique microbiome patterns in saliva from IBD patients and explore potential oral microbial markers for differentiating Crohn’s disease (CD) and ulcerative colitis (UC). A prospective cohort study recruited IBD patients (UC: n = 175, CD: n = 127) and healthy controls (HC: n = 100) to analyze their oral microbiota using 16S rRNA gene sequencing. Machine learning models (sparse partial least squares discriminant analysis (sPLS-DA)) were trained with the sequencing data to classify CD and UC. Taxonomic classification resulted in 4041 phylotypes using Kraken2 and the SILVA reference database. After quality filtering, 398 samples (UC: n = 175, CD: n = 124, HC: n = 99) and 2711 phylotypes were included. Alpha diversity analysis revealed significantly reduced richness in the microbiome of IBD patients compared to healthy controls. The sPLS-DA model achieved high accuracy (mean accuracy: 0.908, and AUC: 0.966) in distinguishing IBD vs. HC, as well as good accuracy (0.846) and AUC (0.923) in differentiating CD vs. UC. These findings highlight distinct oral microbiome patterns in IBD and provide insights into potential diagnostic markers.

In recent years, the importance of microbial diversity and function to ecosystem restoration has been recognized. The aim of this work was to investigate the diversity and composition of bacterial communities in response to reclamation of a soil subsidence area affected by mining activities. Soil samples were taken in two seasons (December 2012 and July 2013) from a mining reclamation region at the Liuxin national reclamation demonstration area in China and an adjacent coal-excavated subsidence region. 454 high-throughput sequencing technology was used to compare the composition and diversity of bacterial communities in reclaimed soil to that in subsided soil. Predominant phyla in soils were Proteobacteria , Actinobacteria , Acidobacteria , and Planctomycetes , with Proteobacteria making up the majority of the community. Long-term reclamation was found to have significant influences on bacterial communities, and the bacterial community diversity and composition varied between reclaimed and subsided soil. Seasonal fluctuations also contributed to variation in soil bacterial diversity and community composition, but were minor in comparison to effects of reclamation. Differences observed in bacterial community structure and diversity were related to both fertilizer treatment and vegetation, likely through the effects of soil attributes. Soil organic matter and total nitrogen and available potassium were important factors shaping the microbial communities. The reclaimed soil had higher community diversity of bacteria than subsided soil, which suggests that long-term applications of organic amendments and vegetation mixed sowing had significant impacts on soil remediation and microbial diversity.

ObjectiveAs laying hens become aged, laying performance and egg quality are generally impaired. One of the practical methods to rejuvenate production and egg quality of aged laying hens with decreasing productivity is a forced molting. However, the changes in intestinal microbiota after forced molting of aged hens are not clearly known. The aim of the present study was to analyze the changes in excreta bacterial communities after forced molting of aged laying hens.MethodsA total of one hundred 66-wk-old Hy-Line Brown laying hens were induced to molt by a 2-d water removal and an 11-d fasting until egg production completely ceased. The excreta samples of 16 hens with similar body weight were collected before and immediately after molting. Excreta bacterial communities were analyzed by high-throughput sequencing of bacterial 16S rRNA genes.ResultsBacteroidetes, Firmicutes, and Proteobacteria were the three major bacterial phyla in pre-molting and immediate post-molting hens, accounting for more than 98.0%. Lactobacillus genus had relatively high abundance in both group, but decreased by molting (62.3% in pre-molting and 24.9% in post-molting hens). Moreover, pathogenic bacteria such as Enterococcus cecorum and Escherichia coli were more abundant in immediate post-molting hens than in pre-molting hens. Forced molting influenced the alpha diversity, with higher Chao1 (p = 0.012), phylogenetic diversity whole tree (p = 0.014), observed operational taxonomic unit indices (p = 0.006), and Simpson indices (p<0.001), which indicated that forced molting increased excreta bacterial richness of aged laying hens.ConclusionThis study improves the current knowledge of bacterial community alterations in the excreta by forced molting in aged laying hens, which can provide increasing opportunity to develop novel dietary and management skills for improving the gastrointestinal health of aged laying hens after molting.

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.

Large numbers of microbes can be present in seminal fluid, and there are differences in the semen microbiota between normal and abnormal semen samples. To evaluate the semen microbiota in patients with leukocytospermia, 87 seminal fluid samples, including 33 samples with a normal seminal leukocyte count and 54 samples with leukocytospermia, were obtained for a cross-sectional analysis. Twenty samples with a normal seminal leukocyte count had normal sperm parameters (Control group), and 13 samples with a normal seminal leukocyte count were from asthenozoospermia patients (Ast group). However, 32 samples with leukocytospermia were from asthenozoospermia patients (LA group), and only 22 samples with leukocytospermia had normal sperm parameters (Leu group). The 16S ribosomal RNA (rRNA) gene sequencing method was used to sequence the microbiota in the seminal fluid, and multiple bioinformatics methods were utilized to analyze the data. Finally, the results showed that the worse sperm parameters were observed in the leukocytospermia-related groups. Semen microbiota analysis found that there was increased alpha diversity in the leukocytospermia-related groups. Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes were the primary phyla in the seminal fluid. Two microbiota profiles, namely, Lactobacillus-enriched and Streptococcus-enriched groups, were identified in this study. The majority of the samples in the groups with a normal seminal leukocyte count could be categorized as Lactobacillus-enriched, whereas the majority of the leukocytospermia samples could be categorized as Streptococcus-enriched. Our study indicated that males with leukocytospermia have worse sperm parameters and a different semen microbiota composition compared to males with a normal seminal leukocyte count.

This study aims for molecular identification of naturally growing strain from a unique source, able to survive, and alleviate heavy metals from the nature. Pure isolate from Murrah buffalo milk was prepared in selective Polymyxin pyruvate egg-yolk mannitol-bromothymol blue agar (PEMBA) medium through a cascade of contamination free subcultures. The morphological and biochemical tests were done prior to 16S rRNA gene sequencing for strain identification and further physiological tests. The test strain was inoculated in both solid and suspension culture medium supplemented individually with Cd, Cu, Ag, and Zn to reveal the qualitative and quantitative heavy metal tolerance properties, respectively. Finally, the data collected from the assessment was statistically analyzed. Molecular analysis revealed that the test strain was BF2, which was motile, catalase positive and Gram positive rod. BF2 was found significant at 0.3% bile salt tolerance [two-way analysis of variance (ANOVA)- value is < 0.0001] where, -test value is < 0.0002 between Control Group (CG) and TGR-1; < 0.037 between TGR-1 and 2; < 0.0014 between CG and TGR-2. Similarly, BF2 was significant in pH tolerant up to 8.0 with < 0.0115 (in scale < 0.05). The heavy metal tolerance test revealed that the test metals could not stop the growth of BF2 even after 24 h of incubation but partially suppressed the growth kinetics for letting into stationary phase. Among the four heavy metals, Cd and Zn showed partial antagonism to the growth of BF2. The survivability was highly significant in the medium supplemented with Zn ( < 0.0001) and Ag ( < 0.018). BF2 can survive in selective heavy metals with metal resistance and biodegradation capacity.

Trees provide organic substrates in the form of root exudates, litterfall, and fine root turnover. They modify soil physical properties and support soil biological activities. Therefore, trees are hypothesized to control soil biodiversity in forested areas. We predicted that (1) experimental forest plantations with higher tree alpha‐diversity have greater soil microbial alpha‐diversity and (2) that plantations with more divergent tree community composition would have more divergent soil microbial assemblages (Whitaker's beta‐diversity). We tested these predictions by measuring soil bacteria and fungi in a 7‐yr‐old tree biodiversity experiment. The experimental plantation contained 37 different tree assemblages, which were composed of one to four native species from temperate mixed deciduous forests. Further, there was a gradient of functional diversity nested within each level of species diversity. Soil samples were assessed for bacteria and fungi by amplicon sequencing. Tree alpha‐diversity weakly, but significantly, affected bacterial alpha‐diversity, without affecting fungal alpha‐diversity. Tree community composition was weakly, but significantly, linked to soil bacterial and fungal assemblages. In these 7‐yr‐old experimental plantations, tree diversity was not the most influential driver of soil microbial diversity.