Comparison of microbial diversity determined with the same variable tag sequence extracted from two different PCR amplicons

Characterization of the equine placental microbial population during nocardioform placentitis

Nocardioform placentitis is a poorly understood disease of equine late gestation. The presence of nocardioform, filamentous branching gram-positive bacteria, has been linked to the disease, with Crossiella equi, Amycolatopsis spp., and Streptomyces spp. being the most frequently identified bacteria. However, these bacteria are not found in all clinical cases in addition to being isolated from healthy, normal postpartum placentas. To better understand this form of placentitis, we analyzed the microbial composition in the equine placenta (chorioallantois) of both healthy postpartum (control; n = 11) and nocardioform-affected samples (n = 22) using 16S rDNA sequencing. We found a lower Shannon index in nocardioform samples, a higher Chao1 index in nocardioform samples, and a difference in beta diversity between control and nocardioform samples (p < 0.05), suggesting the presence of dysbiosis during the disease. In the majority of the NP samples (77 %), one of the following genera-Amycolatopsis, Crossiella, Lentzea, an unidentified member of the Pseudonocardiaceae family, Mycobacterium, or Enterococcus -represented over 70 % of the relative abundance. Overall, the data suggest that a broader spectrum of potential opportunistic pathogens could be involved in nocardioform placentitis, extending beyond the traditionally recognized bacteria, resulting in a similar histomorphological profile.

Microbial diversity and community structure dynamics in acid mine drainage: Acidic fire with dissolved heavy metals

Acid mine drainage (AMD) is one of the leading causes of environmental pollution and is linked to public health and ecological consequences. Microbes-mineral interaction generates AMD, but microorganisms can also remedy AMD pollution. Exploring the microbial response to AMD effluents may reveal survival strategies in extreme ecosystems. Three distinct sites across a mine (inside the mine, the entrance of the mine, and outside) were selected to study their heavy metal concentrations due to significant variations in pH and physicochemical characteristics, and high-throughput sequencing was carried out to investigate the microbial diversity. The metal and ion concentrations followed the order SO42-, Fe, Cu, Zn, Mg, Pb, Co, Cr, and Ni from highest to lowest, respectively. Maximum sequences were allocated to Proteobacteria and Firmicutes. Among archaea, the abundance of Thaumarchaeota and Euryarchaeota was higher outside of mine. Most of the genera (23.12 %) were unclassified and unknown. The average OTUs (operational taxonomic units) were significantly higher outside the mine; however, diversity indices were not significantly different across the mine sites. Hierarchical clustering of selective genera and nMDS ordination of OTUs displayed greater segregation resolution inside and outside of mine, whereas the entrance samples clustered with greater similarity. Heterogeneous selection might be the main driver of community composition outside the mine, whereas stochastic processes became prominent inside the mine. However, the ANOSIM test shows a relatively even distribution of community composition within and between the groups. Microbial phyla showed both positive and negative correlations with physicochemical factors. A greater number of biomarkers were reported outside of the mine. Predictive functional investigation revealed the existence of putative degradative, metabolic, and biosynthetic pathways. This study presents a rare dataset in our understanding of microbial diversity and distribution as shaped by the ecological gradient and potential novelty in phylogenetic/taxonomic diversity in AMD, with potential biotechnological applications.

Freshwater plastispheres as a vector for foodborne bacteria and viruses

There is growing evidence that plastic particles can accumulate microorganisms that are pathogenic to humans or animals. In the current study, the composition of the plastispheres that accumulated on polypropylene (PP), polyvinyl chloride (PVC), and high-density polyethylene (HDPE) pieces submerged in a river in the southeast Norway was characterized by 16S rRNA amplicon sequencing. Seasonal and geographical effects on the bacterial composition of the plastisphere were identified, in addition to the detection of potential foodborne pathogenic bacteria and viruses as part of the plastisphere. The diversity and taxonomic composition of the plastispheres were influenced by the number of weeks in the river, the season, and the location. The bacterial diversity differed significantly in the plastisphere from June and September, with a generally higher diversity in June. Also, the community composition of the plastisphere was significantly influenced by the geographical location, while the type of plastic had less impact. Plastics submerged in river water assembled a variety of microorganisms including potentially pathogenic bacteria and viruses (noro- and adenovirus) detected by qPCR. Cultivation methods detected viable bacteria such as Escherichia coli and Listeria monocytogenes. The results highlight the need for additional research on the risk of contaminating food with plastic particles colonized with human pathogens through irrigation water.

Unveiling the microbiome during post-partum uterine infection: a deep shotgun sequencing approach to characterize the dairy cow uterine microbiome

BACKGROUND

The goal of this study was to assess the microbial ecology and diversity present in the uterus of post-partum dairy cows with and without metritis from 24 commercial California dairy farms using shotgun metagenomics. A set subset of 95 intrauterine swab samples, taken from a larger selection of 307 individual cow samples previously collected, were examined for α and β diversity and differential abundance associated with metritis. Cows within 21 days post-partum were categorized into one of three clinical groups during sample collection: control (CT, n = 32), defined as cows with either no vaginal discharge or a clear, non-purulent mucus vaginal discharge; metritis (MET, n = 33), defined as a cow with watery, red or brown colored, and fetid vaginal discharge; and purulent discharge cows (PUS, n = 31), defined as a non-fetid purulent or mucopurulent vaginal discharge.

RESULTS

All three clinical groups (CT, MET, and PUS) were highly diverse, with the top 12 most abundant genera accounting for 10.3%, 8.8%, and 10.1% of mean relative abundance, respectively. The α diversity indices revealed a lower diversity from samples collected from MET and PUS when compared to CT cows. PERMANOVA statistical testing revealed a significant difference (P adjusted < 0.01) in the diversity of genera between CT and MET samples (R2 = 0.112, P = 0.003) and a non-significant difference between MET and PUS samples (R2 = 0.036, P = 0.046). ANCOM-BC analysis revealed that from the top 12 most abundant genera, seven genera were increased in the natural log fold change (LFC) of abundance in MET when compared to CT samples: Bacteroides, Clostridium, Fusobacterium, Phocaeicola, Porphyromonas, Prevotella, and Streptococcus. Two genera, Dietzia and Microbacterium, were decreased in natural LFC of abundance when comparing MET (regardless of treatment) and CT, while no changes in natural LFC of abundance were observed for Escherichia, Histophilus, and Trueperella.

CONCLUSIONS

The results presented here, are the current deepest shotgun metagenomic analyses conducted on the bovine uterine microbiome to date (mean of 256,425 genus-level reads per sample). Our findings support that uterine samples from cows without metritis (CT) had increased α-diversity but decreased β-diversity when compared to metritis or PUS cows, characteristic of dysbiosis. In summary, our findings highlight that MET cows have an increased abundance of Bacteroides, Porphyromonas, and Fusobacterium when compared to CT and PUS, and support the need for further studies to better understand their potential causal role in metritis pathogenesis.

Whey and Buttermilk-Based Formulas Modulate Gut Microbiota in Mice with Antibiotic-Induced Dysbiosis

SCOPE

Diet is one of the main factors that modifies intestinal microbiota composition. The search for foods that can reverse situations of intestinal dysbiosis such as that induced by antibiotics is of great interest. Buttermilk and whey are the main by-products produced by the dairy industry containing bioactive compounds. The aim of this study is to investigate the ability of whey and buttermilk-based formulas supplemented with lactoferrin and milk fat globule membrane (MFGM) to modulate the effects of clindamycin on mouse intestinal microbiota.

METHODS AND RESULTS

Male C57BL/6 mice are treated with saline (control), clindamycin (Clin), a formula containing whey (F1) or buttermilk (F2), Clin+F1 or Clin+F2, and their fecal microbiota profiles are analyzed by sequencing of 16S rRNA gene using the MinION device. Clin induces alterations in both the composition and metabolic functions of the mice intestinal microbiota. The treatment with F1 or F2 reverses the effects of clindamycin, restoring the levels of Rikenellaceae and Lactobacillaceae families and certain pathways related to short-chain fatty acids production and tetrahydrofolate biosynthesis.

CONCLUSION

Whey and buttermilk supplemented with lactoferrin and MFGM may be a bioactive formula for functional foods to prevent or restore microbiota alterations induced by antibiotic administration.

Amplicon Sequencing Reveals Complex Infection in Infants Congenitally Infected With Trypanosoma Cruzi and Informs the Dynamics of Parasite Transmission

Congenital transmission of Trypanosoma cruzi is an important source of new Chagas infections worldwide. The mechanisms of congenital transmission remain poorly understood, but there is evidence that parasite factors are involved. Investigating changes in parasite strain diversity during transmission could provide insight into the parasite factors that influence the process. Here we use amplicon sequencing of a single copy T. cruzi gene to evaluate the diversity of infection in clinical samples from Chagas positive mothers and their infected infants. Several infants and mothers were infected with multiple parasite strains, mostly of the same TcV lineage, and parasite strain diversity was higher in infants than mothers. Two parasite haplotypes were detected exclusively in infant samples, while one haplotype was never found in infants. Together, these data suggest multiple parasites initiate a congenital infection and that parasite factors influence the probability of vertical transmission.

Gut dysbiosis in Thai intrahepatic cholangiocarcinoma and hepatocellular carcinoma

Primary liver cancer (PLC), which includes intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC), has the highest incidence of all cancer types in Thailand. Known etiological factors, such as viral hepatitis and chronic liver disease do not fully account for the country's unusually high incidence. However, the gut-liver axis, which contributes to carcinogenesis and disease progression, is influenced by the gut microbiome. To investigate this relationship, fecal matter from 44 Thai PLC patients and 76 healthy controls were subjected to whole-genome metagenomic shotgun sequencing and then analyzed by marker gene-based and assembly based methods. Results revealed greater gut microbiome heterogeneity in iCCA compared to HCC and healthy controls. Two Veillonella species were found to be more abundant in iCCA samples and could distinguish iCCA from HCC and healthy controls. Conversely, Ruminococcus gnavus was depleted in iCCA patients and could distinguish HCC from iCCA samples. High Veillonella genus counts in the iCCA group were associated with enriched amino acid biosynthesis and glycolysis pathways, while enriched phospholipid and thiamine metabolism pathways characterized the HCC group with high Blautia genus counts. These findings reveal distinct landscapes of gut dysbiosis among Thai iCCA and HCC patients and warrant further investigation as potential biomarkers.

Exploring breast tissue microbial composition and the association with breast cancer risk factors

BACKGROUND

Microbial dysbiosis has emerged as an important element in the development and progression of various cancers, including breast cancer. However, the microbial composition of the breast from healthy individuals, even relative to risk of developing breast cancer, remains unclear. Here, we performed a comprehensive analysis of the microbiota of the normal breast tissue, which was analyzed in relation to the microbial composition of the tumor and adjacent normal tissue.

METHODS

The study cohorts included 403 cancer-free women (who donated normal breast tissue cores) and 76 breast cancer patients (who donated tumor and/or adjacent normal tissue samples). Microbiome profiling was obtained by sequencing the nine hypervariable regions of the 16S rRNA gene (V1V2, V2V3, V3V4, V4V5, V5V7, and V7V9). Transcriptome analysis was also performed on 190 normal breast tissue samples. Breast cancer risk score was assessed using the Tyrer-Cuzick risk model.

RESULTS

The V1V2 amplicon sequencing resulted more suitable for the analysis of the normal breast microbiome and identified Lactobacillaceae (Firmicutes phylum), Acetobacterraceae, and Xanthomonadaceae (both Proteobacteria phylum) as the most abundant families in the normal breast. However, Ralstonia (Proteobacteria phylum) was more abundant in both breast tumors and histologically normal tissues adjacent to malignant tumors. We also conducted a correlation analysis between the microbiome and known breast cancer risk factors. Abundances of the bacterial taxa Acetotobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp. were associated with age (p < 0.0001), racial background (p < 0.0001), and parity (p < 0.0001). Finally, transcriptome analysis of normal breast tissues showed an enrichment in metabolism- and immune-related genes in the tissues with abundant Acetotobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp., whereas the presence of Ralstonia in the normal tissue was linked to dysregulation of genes involved in the carbohydrate metabolic pathway.

CONCLUSIONS

This study defines the microbial features of normal breast tissue, thus providing a basis to understand cancer-related dysbiosis. Moreover, the findings reveal that lifestyle factors can significantly affect the normal breast microbial composition.

Soil Bacterial Assemblage Across a Production Landscape: Agriculture Increases Diversity While Revegetation Recovers Community Composition

Aboveground ecological impacts associated with agricultural land use change are evident as natural plant communities are replaced with managed production systems. These impacts have been extensively studied, unlike those belowground, which remain poorly understood. Soil bacteria are good candidates to monitor belowground ecological dynamics due to their prevalence within the soil system and ability to survive under harsh and changing conditions. Here, we use soil physicochemical assessment and 16S rRNA gene sequencing to investigate the soil physical and bacterial assemblage changes across a mixed-use agricultural landscape. We assess soil from remnant vegetation (Eucalyptus mallee), new and old vineyards, old pasture, and recently revegetated areas. Elevated concentrations of nitrogen (NO₃^-) and plant-available (Colwell) phosphorus were identified in the managed vineyard systems, highlighting the impact of agricultural inputs on soil nutrition. Alpha diversity comparison revealed a significant difference between the remnant mallee vegetation and the vineyard systems, with vineyards supporting highest bacterial diversity. Bacterial community composition of recently revegetated areas was similar to remnant vegetation systems, suggesting that bacterial communities can respond quickly to aboveground changes, and that actions taken to restore native plant communities may also act to recover natural microbial communities, with implications for soil and plant health. Findings here suggest that agriculture may disrupt the correlation between above- and belowground diversities by altering the natural processes that otherwise govern this relationship (e.g. disturbance, plant production, diversity of inputs), leading to the promotion of belowground microbial diversity in agricultural systems.

Gut and airway microbiota dysbiosis and their role in COVID-19 and long-COVID

The gut microbiota plays a crucial role in human health and disease. Gut dysbiosis is known to be associated with increased susceptibility to respiratory diseases and modifications in the immune response and homeostasis of the lungs (the so-called gut-lung axis). Furthermore, recent studies have highlighted the possible role of dysbiosis in neurological disturbances, introducing the notion of the "gut-brain axis." During the last 2 years, several studies have described the presence of gut dysbiosis during coronavirus disease 2019 (COVID-19) and its relationship with disease severity, SARS-CoV-2 gastrointestinal replication, and immune inflammation. Moreover, the possible persistence of gut dysbiosis after disease resolution may be linked to long-COVID syndrome and particularly to its neurological manifestations. We reviewed recent evidence on the association between dysbiosis and COVID-19, investigating the possible epidemiologic confounding factors like age, location, sex, sample size, the severity of disease, comorbidities, therapy, and vaccination status on gut and airway microbial dysbiosis in selected studies on both COVID-19 and long-COVID. Moreover, we analyzed the confounding factors strictly related to microbiota, specifically diet investigation and previous use of antibiotics/probiotics, and the methodology used to study the microbiota (α- and β-diversity parameters and relative abundance tools). Of note, only a few studies focused on longitudinal analyses, especially for long-term observation in long-COVID. Lastly, there is a lack of knowledge regarding the role of microbiota transplantation and other therapeutic approaches and their possible impact on disease progression and severity. Preliminary data seem to suggest that gut and airway dysbiosis might play a role in COVID-19 and in long-COVID neurological symptoms. Indeed, the development and interpretation of these data could have important implications for future preventive and therapeutic strategies.

Community diversity is associated with intra-species genetic diversity and gene loss in the human gut microbiome

How the ecological process of community assembly interacts with intra-species diversity and evolutionary change is a longstanding question. Two contrasting hypotheses have been proposed: Diversity Begets Diversity (DBD), in which taxa tend to become more diverse in already diverse communities, and Ecological Controls (EC), in which higher community diversity impedes diversification. Previously, using 16S rRNA gene amplicon data across a range of microbiomes, we showed a generally positive relationship between taxa diversity and community diversity at higher taxonomic levels, consistent with the predictions of DBD (Madi et al., 2020). However, this positive 'diversity slope' plateaus at high levels of community diversity. Here we show that this general pattern holds at much finer genetic resolution, by analyzing intra-species strain and nucleotide variation in static and temporally sampled metagenomes from the human gut microbiome. Consistent with DBD, both intra-species polymorphism and strain number were positively correlated with community Shannon diversity. Shannon diversity is also predictive of increases in polymorphism over time scales up to ~4-6 months, after which the diversity slope flattens and becomes negative - consistent with DBD eventually giving way to EC. Finally, we show that higher community diversity predicts gene loss at a future time point. This observation is broadly consistent with the Black Queen Hypothesis, which posits that genes with functions provided by the community are less likely to be retained in a focal species' genome. Together, our results show that a mixture of DBD, EC, and Black Queen may operate simultaneously in the human gut microbiome, adding to a growing body of evidence that these eco-evolutionary processes are key drivers of biodiversity and ecosystem function.

A metagenomic analysis of the bacterial microbiome of limestone, and the role of associated biofilms in the biodeterioration of heritage stone surfaces

There is growing concern surrounding the aesthetic and physical effects of microbial biofilms on heritage buildings and monuments. Carboniferous stones, such as limestone and marble, are soluble in weak acid solutions and therefore particularly vulnerable to biocorrosion. This paper aims to determine the differences and commonalities between the microbiome of physically damaged and undamaged Lincolnshire limestone, an area of research which has not been previously studied. A lack of information about the core microbiome has resulted in conflicting claims in the literature regarding the biodeteriorative potential of many microorganisms. To address this, we used metagenomics alongside traditional microbiological techniques to produce an in-depth analysis of differences between the bacterial microbiomes found on deteriorated and undamaged external limestone surfaces. We demonstrate there is a core microbiome on Lincolnshire limestone present on both damaged and undamaged surfaces. In addition to the core microbiome, significant differences were found between species isolated from undamaged compared to damaged surfaces. Isolated species were characterised for biofilm formation and biodeteriorative processes, resulting in the association of species with biodeterioration that had not been previously described. Additionally, we have identified a previously undescribed method of biofilm-associated biomechanical damage. This research adds significant new understanding to the field, aiding decision making in conservation of stone surfaces.

Enzymatic biodegradation of highly p-xylene contaminated soil using cold-active enzymes: A soil column study

Enzymatic bioremediation is a sustainable and environment-friendly method for the clean-up of contaminated soil and water. In the present study, enzymatic bioremediation was designed using cold-active enzymes (psychrozymes) which catalyze oxidation steps of p-xylene biodegradation in highly contaminated soil (initial concentration of 13,000 mg/kg). The enzymes were obtained via co-culture of two psychrophilic Pseudomonas strains and characterized by kinetic studies and tandem LC-MS/MS. To mimic in situ application of enzyme mixture, bioremediation of p-xylene contaminated soil was carried out in soil column (140 mL) tests with the injection (3 pore volume) of different concentrations of enzyme cocktails (X, X/5, and X/10). Enzyme cocktail in X concentration contained about 10 U/mL of xylene monooxygenase (XMO) and 20 U/mL of catechol 2, 3 dioxygenases (C2,3D). X/5 and X/10 correspond to 5x and 10x dilution of enzyme cocktail respectively. The results showed that around 92-94% p-xylene removal was achieved in the treated soil column with enzyme concentration X, X/5 after second enzyme injection. While the p-xylene removal rate obtained by X/10 concentration of enzyme was less than 30% and near to untreated soil column (22.2%). The analysis of microbial diversity and biotoxicity assay (root elongation and seed germination) confirmed the advantage of using enzymes as a green and environmentally friendly approach for decontamination of pollutants with minimal or even positive effects on microbial community and also enrichment of soil after treatment.

Effect of heat stress on ileal microbial community of indigenous yellow-feather broilers based on 16S rRNA gene sequencing

Objectives

The broiler chickens are susceptible to heat stress (HS), including the indigenous broilers raised in tropical and subtropical regions. HS caused intestinal dysfunction and disrupted the gut microbiota. However, the researches about the effects of HS on ileal microbiome of indigenous broilers are limited. Therefore, this experiment used 16S rRNA sequencing to analyse the ileal microbial community in indigenous yellow‐feather broilers under HS.

Material and methods

The single factor completely random design was used in the present study, and forty 8‐week‐old Chinese indigenous yellow‐feather broilers (Huaixiang chickens) were randomly divided into two treatments: normal temperature (NT) group and HS group. There are five replications with four broilers per replicate in each group. The broilers in NT group were raised at 21.3 ± 1.2°C during the whole experimental period, the broilers in HS group were exposed to 32.5 ± 1.4°C for 8 h/day from 9:00 am to 17:00 pm and the temperature of rest time is consistent with NT group. The experiment lasted for 4 weeks.

Results

The results showed that HS exposure had no significant effects on the alpha diversity index of ileal microflora of broilers, including the Shannon, Simpson, Chao1 and ACE indexes (p > 0.05). At the genus level, HS significantly reduced the relative abundance of Campylobacter (p < 0.05), and increased the abundance of Delftia (p < 0.05). In addition, prediction of microbial community function indicated that HS significantly enhanced the abundance of the microflora related to lipid metabolism, carbohydrate metabolism and xenobiotics biodegradation and metabolism and reduced the abundance of the microflora related to nucleotide metabolism and amino acid metabolism.

Conclusions

Taken together, the present study revealed that chronic HS (4 weeks) exposure changes the abundance of the ileal microflora of broilers. These findings provided new insights into the role of HS in influencing ileal microbial community in indigenous broilers.

Ammonia-oxidizing bacterial communities are affected by nitrogen fertilization and grass species in native C4 grassland soils

Background

Fertilizer addition can contribute to nitrogen (N) losses from soil by affecting microbial populations responsible for nitrification. However, the effects of N fertilization on ammonia oxidizing bacteria under C₄ perennial grasses in nutrient-poor grasslands are not well studied.

Methods

In this study, a field experiment was used to assess the effects of N fertilization rate (0, 67, and 202 kg N ha⁻¹) and grass species (switchgrass (Panicum virgatum) and big bluestem (Andropogon gerardii)) on ammonia-oxidizing bacterial (AOB) communities in C₄ grassland soils using quantitative PCR, quantitative reverse transcription-PCR, and high-throughput amplicon sequencing of amoA genes.

Results

Nitrosospira were dominant AOB in the C₄ grassland soil throughout the growing season. N fertilization rate had a stronger influence on AOB community composition than C₄ grass species. Elevated N fertilizer application increased the abundance, activity, and alpha-diversity of AOB communities as well as nitrification potential, nitrous oxide (N₂O) emission and soil acidity. The abundance and species richness of AOB were higher under switchgrass compared to big bluestem. Soil pH, nitrate, nitrification potential, and N₂O emission were significantly related to the variability in AOB community structures (p < 0.05).

Diversity and Taxonomic Distribution of Endophytic Bacterial Community in the Rice Plant and Its Prospective

Endophytic bacterial communities are beneficial communities for host plants that exist inside the surfaces of plant tissues, and their application improves plant growth. They benefit directly from the host plant by enhancing the nutrient amount of the plant’s intake and influencing the phytohormones, which are responsible for growth promotion and stress. Endophytic bacteria play an important role in plant-growth promotion (PGP) by regulating the indirect mechanism targeting pest and pathogens through hydrolytic enzymes, antibiotics, biocontrol potential, and nutrient restriction for pathogens. To attain these benefits, firstly bacterial communities must be colonized by plant tissues. The nature of colonization can be achieved by using a set of traits, including attachment behavior and motility speed, degradation of plant polymers, and plant defense evasion. The diversity of bacterial endophytes colonization depends on various factors, such as plants’ relationship with environmental factors. Generally, each endophytic bacteria has a wide host range, and they are used as bio-inoculants in the form of synthetic applications for sustainable agriculture systems and to protect the environment from chemical hazards. This review discusses and explores the taxonomic distribution of endophytic bacteria associated with different genotypes of rice plants and their origin, movement, and mechanism of PGP. In addition, this review accentuates compressive meta data of endophytic bacteria communities associated with different genotypes of rice plants, retrieves their plant-growth-promoting properties and their antagonism against plant pathogens, and discusses the indication of endophytic bacterial flora in rice plant tissues using various methods. The future direction deepens the study of novel endophytic bacterial communities and their identification from rice plants through innovative techniques and their application for sustainable agriculture systems.

Local versus site-level effects of algae on coral microbial communities

Microbes influence ecological processes, including the dynamics and health of macro-organisms and their interactions with other species. In coral reefs, microbes mediate negative effects of algae on corals when corals are in contact with algae. However, it is unknown whether these effects extend to larger spatial scales, such as at sites with high algal densities. We investigated how local algal contact and site-level macroalgal cover influenced coral microbial communities in a field study at two islands in French Polynesia, Mo'orea and Mangareva. At 5 sites at each island, we sampled prokaryotic microbial communities (microbiomes) associated with corals, macroalgae, turf algae and water, with coral samples taken from individuals that were isolated from or in contact with turf or macroalgae. Algal contact and macroalgal cover had antagonistic effects on coral microbiome alpha and beta diversity. Additionally, coral microbiomes shifted and became more similar to macroalgal microbiomes at sites with high macroalgal cover and with algal contact, although the microbial taxa that changed varied by island. Our results indicate that coral microbiomes can be affected by algae outside of the coral's immediate vicinity, and local- and site-level effects of algae can obscure each other's effects when both scales are not considered.

Gut Microbiota in Mexican Children With Acute Diarrhea: An Observational Study

BACKGROUND

Acute diarrhea is the second leading cause of preventable mortality and morbidity in children worldwide. This study aimed to identify the main pathogens associated with acute diarrhea and to describe changes in gut microbiota in Mexican children.

METHODS

This single-center observational study included 30 children (6 months to 5 years old) with acute diarrhea who were referred to the Instituto Nacional de Pediatría of Mexico City and 15 healthy volunteers (control group). Stool samples at day 0 (D0) and day 15 (D15) were collected for identification of microorganisms (reverse transcriptase-polymerase chain reaction analyses with xTAG gastrointestinal pathogen panel multiplex assay) and microbiota analysis (16S gene amplification sequencing). Prescription decisions were made by the treating clinician.

RESULTS

The main pathogens identified were norovirus and Campylobacter jejuni (20% each). The majority of patients (n = 24) were prescribed Saccharomyces boulardii CNCM I-745 for treatment of acute diarrhea. Diarrheic episodes resolved within 1 week of treatment. Compared with D15 and control samples, D0 samples showed significantly lower alpha diversity and a clear shift in overall composition (beta diversity). Alpha diversity was significantly increased in S. boulardii-treated group between D0 and D15 to a level similar to that of control group.

CONCLUSIONS

In these children, acute diarrhea was accompanied by significant alterations in gut microbiota. S. boulardii CNCM I-745 treatment may facilitate gut microbiota restoration in children with acute diarrhea, mostly through improvements in alpha diversity.

Comprehensive single-PCR 16S and 18S rRNA community analysis validated with mock communities, and estimation of sequencing bias against 18S

Universal primers for SSU rRNA genes allow profiling of natural communities by simultaneously amplifying templates from Bacteria, Archaea, and Eukaryota in a single PCR reaction. Despite the potential to show relative abundance for all rRNA genes, universal primers are rarely used, due to various concerns including amplicon length variation and its effect on bioinformatic pipelines. We thus developed 16S and 18S rRNA mock communities and a bioinformatic pipeline to validate this approach. Using these mocks, we show that universal primers (515Y/926R) outperformed eukaryote-specific V4 primers in observed versus expected abundance correlations (slope = 0.88 vs. 0.67-0.79), and mock community members with single mismatches to the primer were strongly underestimated (threefold to eightfold). Using field samples, both primers yielded similar 18S beta-diversity patterns (Mantel test, p < 0.001) but differences in relative proportions of many rarer taxa. To test for length biases, we mixed mock communities (16S + 18S) before PCR and found a twofold underestimation of 18S sequences due to sequencing bias. Correcting for the twofold underestimation, we estimate that, in Southern California field samples (1.2-80 μm), there were averages of 35% 18S, 28% chloroplast 16S, and 37% prokaryote 16S rRNA genes. These data demonstrate the potential for universal primers to generate comprehensive microbiome profiles.

Bacterial Diversity and Communities Structural Dynamics in Soil and Meltwater Runoff at the Frontier of Baishui Glacier No.1, China

Comprehensive knowledge of bacterial ecology mainly in supraglacial habitats is pivotal particularly at the frontier of accelerated glacier retreat. In this study, bacterial diversity and community composition in glacial soil and meltwater runoff at the frontier of Baishui Glacier No.1 were evaluated using high throughput sequencing. Significant variations in the physiochemical parameters formed an ecological gradient between soil and meltwater runoff. Based on the richness and evenness indexes, the bacterial diversity was relatively higher in soil compared with meltwater runoff. Hierarchical clustering and bi-plot ordination revealed that the taxonomic composition of soil samples was highly similar and significantly influenced by the ecological parameters than the meltwater runoff. The overall relative abundance trend of bacterial phyla and genera were greatly varied in soil and water samples. The relative abundance of Proteobacteria was higher in water runoff samples (40.5-87%) compared with soil samples (32-52.7%). Proteobacteria, Firmicutes, and a little part of Cyanobacteria occupied a major portion of water runoff while the soil was dominated by Acidobacteria (6-16.2%), Actinobacteria (5-16%), Bacteroidetes (0.5-8.8%), and Cyanobacteria (0.1-8.3%) besides Proteobacteria and Firmicutes. Higher numbers of biomarkers were found in soil group compared with the water group. The study area is diverse in terms of richness, while community structures are not evenly distributed. This study provides a preliminary understanding of the bacterial diversity and shifts in community structure in soil and meltwater runoff at the frontier of the glacial. The findings revealed that the environmental factors are a significantly strong determinant of bacterial community structures in such a closely linked ecosystem.

Microbial dysbiosis and polyamine metabolism as predictive markers for early detection of pancreatic cancer

The lack of tools for early detection of pancreatic ductal adenocarcinoma (PDAC) is directly correlated with the abysmal survival rates in patients. In addition to several potential detection tools under active investigation, we tested the gut microbiome and its metabolic complement as one of the earliest detection tools that could be useful in patients at high risk for PDAC. We used a combination of 16s rRNA pyrosequencing and whole-genome sequencing of gut fecal microbiota in a genetically engineered PDAC murine model (KRASG12DTP53R172HPdxCre or KPC). Metabolic reconstruction of microbiome was done using the HUMAnN2 pipeline. Serum polyamine levels were measured from murine and patient samples using chromogenic assay. Our results showed a Proteobacterial and Firmicutes dominance in gut microbiota in early stages of PDAC development. Upon in silico reconstruction of active metabolic pathways within the altered microbial flora, polyamine and nucleotide biosynthetic pathways were significantly elevated. These metabolic products are known to be actively assimilated by the host and eventually utilized by rapidly dividing cells for proliferation validating their importance in the context of tumorigenesis. In KPC mice, as well as PDAC patients, we show significantly elevated serum polyamine concentrations. Therefore, at the early stages of tumorigenesis, there is a strong correlation between microbial changes and release of metabolites that foster host tumorigenesis, thereby fulfilling the 'vicious cycle hypothesis' of the role of microbiome in health and disease states. Our results provide a potential, precise, noninvasive tool for early detection of PDAC, which may result in improved outcomes.

Differentiation strategies of soil rare and abundant microbial taxa in response to changing climatic regimes

Despite the important roles of soil microbes, especially the most diverse rare taxa in maintaining community diversity and multifunctionality, how different climate regimes alter the stability and functions of the rare microbial biosphere remains unknown. We reciprocally transplanted field soils across a latitudinal gradient to simulate climate change and sampled the soils annually after harvesting the maize over the following 6 years (from 2005 to 2011). By sequencing microbial 16S ribosomal RNA gene amplicons, we found that changing climate regimes significantly altered the composition and dynamics of soil microbial communities. A continuous succession of the rare and abundant communities was observed. Rare microbial communities were more stable under changing climatic regimes, with lower variations in temporal dynamics, and higher stability and constancy of diversity. More nitrogen cycling genes were detected in the rare members than in the abundant members, including amoA, napA, nifH, nirK, nirS, norB and nrfA. Random forest analysis and receiver operating characteristics analysis showed that rare taxa may act as potential contributors to maize yield under changing climatics. The study indicates that the taxonomically and functionally diverse rare biosphere has the potential to increase functional redundancy and enhance the ability of soil communities to counteract environmental disturbances. With ongoing global climate change, exploring the succession process and functional changes of rare taxa may be important in elucidating the ecosystem stability and multifunctionality that are mediated by microbial communities.

Development of an autonomous biosampler to capture in situ aquatic microbiomes

The importance of planktonic microbial communities is well acknowledged, since they are fundamental for several natural processes of aquatic ecosystems. Microorganisms naturally control the flux of nutrients, and also degrade and recycle anthropogenic organic and inorganic contaminants. Nevertheless, climate change effects and/or the runoff of nutrients/pollutants can affect the equilibrium of natural microbial communities influencing the occurrence of microbial pathogens and/or microbial toxin producers, which can compromise ecosystem environmental status. Therefore, improved microbial plankton monitoring is essential to better understand how these communities respond to environmental shifts. The study of marine microbial communities typically involves highly cost and time-consuming sampling procedures, which can limit the frequency of sampling and data availability. In this context, we developed and validated an in situ autonomous biosampler (IS-ABS) able to collect/concentrate in situ planktonic communities of different size fractions (targeting prokaryotes and unicellular eukaryotes) for posterior genomic, metagenomic, and/or transcriptomic analysis at a home laboratory. The IS-ABS field prototype is a small size and compact system able to operate up to 150 m depth. Water is pumped by a micropump (TCS MG2000) through a hydraulic circuit that allows in situ filtration of environmental water in one or more Sterivex filters placed in a filter cartridge. The IS-ABS also includes an application to program sampling definitions, allowing pre-setting configuration of the sampling. The efficiency of the IS-ABS was tested against traditional laboratory filtration standardized protocols. Results showed a good performance in terms of DNA recovery, as well as prokaryotic (16S rDNA) and eukaryotic (18S rDNA) community diversity analysis, using either methodologies. The IS-ABS automates the process of collecting environmental DNA, and is suitable for integration in water observation systems, what will contribute to substantially increase biological surveillances. Also, the use of highly sensitive genomic approaches allows a further study of the diversity and functions of whole or specific microbial communities.

Agricultural Risk Factors Influence Microbial Ecology in Honghu Lake

Agricultural activities, including stock-farming, planting industry, and fish aquaculture, can affect the physicochemical and biological characters of freshwater lakes. However, the effects of pollution producing by agricultural activities on microbial ecosystem of lakes remain unclear. Hence, in this work, we selected Honghu Lake as a typical lake that is influenced by agriculture activities. We collected water and sediment samples from 18 sites, which span a wide range of areas from impacted and less-impacted areas. We performed a geospatial analysis on the composition of microbial communities associated with physicochemical properties and antibiotic pollution of samples. The co-occurrence networks of water and sediment were also built and analyzed. Our results showed that the microbial communities of impacted and less-impacted samples of water were largely driven by the concentrations of TN, TP, NO₃⁻-N, and NO₂⁻-N, while those of sediment were affected by the concentrations of Sed-OM and Sed-TN. Antibiotics have also played important roles in shaping these microbial communities: the concentrations of oxytetracycline and tetracycline clearly reflected the variance in taxonomic diversity and predicted functional diversity between impacted and less-impacted sites in water and sediment samples, respectively. Furthermore, for samples from both water and sediment, large differences of network topology structures between impacted and less-impacted were also observed. Our results provide compelling evidence that the microbial community can be used as a sentinel of eutrophication and antibiotics pollution risk associated with agricultural activity; and that proper monitoring of this environment is vital to maintain a sustainable environment in Honghu Lake.

Characterization of human breast tissue microbiota from core needle biopsies through the analysis of multi hypervariable 16S-rRNA gene regions

Breast microbiota compositions are not well understood, and a few recent reports have begun to explore the correlation between breast tissue dysbiosis and cancer. Given that various methods for breast microbiota detection were used, the aim of the present paper was to clarify which hypervariable region of the 16S-rRNA gene (V2, V3, V4, V6 + 7, V8, and V9) is the most informative for breast tissue microbiota. Core needle biopsies (CNBs) were compared with surgical excision biopsies (SEBs) to find a less invasive form of recovery useful for the analysis of a larger statistical population and potentially for diagnostic use of breast tissue microbiota. Finally, this study was the first to analyse the breast microbiota of tumours and paired normal tissues of a Mediterranean population. Our findings showed that the V3 region is the most informative for breast tissue microbiota, accounting for 45% of all reads. No significant differences were found between CNB and SEB specimens in terms of total reads and numbers of Operational Taxonomic Units (OTUs). Moreover, we find that more similarities than differences exist between tumours and adjacent normal tissues. Finally, the presence of the Ralstonia genus is associated with breast tissue.

Effects of antibiotic on microflora in ileum and cecum for broilers by 16S rRNA sequence analysis

An experiment was conducted to analyze and compare the microbial composition, abundance, dynamic distribution, and functions without and with antibiotic fed to broilers. A 16S rRNA-sequencing approach was used to evaluate the bacterial composition of the gut of male broilers under different groups. A total of 240 1-day old AA male broilers were randomly assigned to two groups, with 120 broilers per group. The treatment group was administered an antibiotic with their feed, while the control group was not administered antibiotic (control group). A total of 10 replicates were assessed per treatment. The control group was fed a basal diet containing corn, soybean meal, and cottonseed meal and met the nutritional requirement. The antibiotic group was fed 100 mg/kg aureomycin (based on the basal diet). The trial lasted 42 days. Operational taxonomic unit partition and classification, alpha diversity, taxonomic composition, beta diversity, and microflora comparative analyses along with key species screening were performed for all of the treatment groups. Our data indicate that aureomycin treatment in broilers is directly correlated with variations of the gut content of specific bacterial taxa, and herein provide insights into the impact of antibiotic on microbial communities in cecum and ileum of broiler chickens.

Hypothesis Testing and Statistical Analysis of Microbiome

After the initiation of Human Microbiome Project in 2008, various biostatistic and bioinformatic tools for data analysis and computational methods have been developed and applied to microbiome studies. In this review and perspective, we discuss the research and statistical hypotheses in gut microbiome studies, focusing on mechanistic concepts that underlie the complex relationships among host, microbiome, and environment. We review the current available statistic tools and highlight recent progress of newly developed statistical methods and models. Given the current challenges and limitations in biostatistic approaches and tools, we discuss the future direction in developing statistical methods and models for the microbiome studies.

Oropharyngeal and Sputum Microbiomes Are Similar Following Exacerbation of Chronic Obstructive Pulmonary Disease

Growing evidence suggests that the airway microbiota might be involved in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Understanding this relationship requires examination of a large-scale population for a long duration to accurately monitor changes in the microbiome. This type of longitudinal study requires an appropriate sampling strategy; two options are the collection of sputum or oropharyngeal swabs. Comparative analysis of the changes that occur in these two specimen types has not been previously performed. This observational study was conducted to explore oropharyngeal microbial community dynamics over time and to examine the relationship between oropharyngeal swabs and sputum. A total of 114 samples were collected from four patients suffering from severe AECOPD. Bacterial and fungal communities were evaluated using 16S rRNA and ITS sequencing. Inter-individual differences were found in bacterial community structure, but the core genera were shared by both sample types and included 32 lineages. Most of the core genera were members of the phyla Proteobacteria, Firmicutes and Ascomycota. Although the oropharyngeal samples showed higher bacterial alpha diversity, the two sample types generated rather similar taxonomic profiles. These results suggest that the sputum microbiome is remarkably similar to the oropharyngeal microbiome. Thus, oropharyngeal swabs can potentially be used instead of sputum samples for patients with exacerbation of COPD.

NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes

Background Massive high-throughput sequencing of short, hypervariable segments of the 16S ribosomal RNA (rRNA) gene has transformed the methodological landscape describing microbial diversity within and across complex biomes. However, several studies have shown that the methodology rather than the biological variation is responsible for the observed sample composition and distribution. This compromises true meta-analyses, although this fact is often disregarded. Results To facilitate true meta-analysis of microbiome studies, we developed NG-Tax, a pipeline for 16S rRNA gene amplicon sequence analysis that was validated with different mock communities and benchmarked against QIIME as the currently most frequently used pipeline. The microbial composition of 49 independently amplified mock samples was characterized by sequencing two variable 16S rRNA gene regions, V4 and V5-V6, in three separate sequencing runs on Illumina's HiSeq2000 platform. This allowed evaluating important factors of technical bias in taxonomic classification: 1) run-to-run sequencing variation, 2) PCR-error, and 3) region/primer specific amplification bias. Despite the short read length (~140 nt) and all technical biases, the average specificity of the taxonomic assignment for the phylotypes included in the mock communities was 96%. On average 99.94% and 92.02% of the reads could be assigned to at least family or genus level, respectively, while assignment to 'spurious genera' represented on average only 0.02% of the reads per sample. Analysis of α- and β-diversity confirmed conclusions guided by biology rather than the aforementioned methodological aspects, which was not the case when samples were analysed using QIIME. Conclusions Different biological outcomes are commonly observed due to 16S rRNA region-specific performance. NG-Tax demonstrated high robustness against choice of region and other technical biases associated with 16S rRNA gene amplicon sequencing studies, diminishing their impact and providing accurate qualitative and quantitative representation of the true sample composition. This will improve comparability between studies and facilitate efforts towards standardization.

NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes

Background: Massive high-throughput sequencing of short, hypervariable segments of the 16S ribosomal RNA (rRNA) gene has transformed the methodological landscape describing microbial diversity within and across complex biomes. However, several studies have shown that the methodology rather than the biological variation is responsible for the observed sample composition and distribution. This compromises meta-analyses, although this fact is often disregarded. Results: To facilitate true meta-analysis of microbiome studies, we developed NG-Tax, a pipeline for 16S rRNA gene amplicon sequence analysis that was validated with different mock communities and benchmarked against QIIME as a frequently used pipeline. The microbial composition of 49 independently amplified mock samples was characterized by sequencing two variable 16S rRNA gene regions, V4 and V5-V6, in three separate sequencing runs on Illumina's HiSeq2000 platform. This allowed for the evaluation of important causes of technical bias in taxonomic classification: 1) run-to-run sequencing variation, 2) PCR-error, and 3) region/primer specific amplification bias. Despite the short read length (~140 nt) and all technical biases, the average specificity of the taxonomic assignment for the phylotypes included in the mock communities was 97.78%. On average 99.95% and 88.43% of the reads could be assigned to at least family or genus level, respectively, while assignment to 'spurious genera' represented on average only 0.21% of the reads per sample. Analysis of α- and β-diversity confirmed conclusions guided by biology rather than the aforementioned methodological aspects, which was not achieved with QIIME. Conclusions: Different biological outcomes are commonly observed due to 16S rRNA region-specific performance. NG-Tax demonstrated high robustness against choice of region and other technical biases associated with 16S rRNA gene amplicon sequencing studies, diminishing their impact and providing accurate qualitative and quantitative representation of the true sample composition. This will improve comparability between studies and facilitate efforts towards standardization.

Development of an Analysis Pipeline Characterizing Multiple Hypervariable Regions of 16S rRNA Using Mock Samples

Objectives

There is much speculation on which hypervariable region provides the highest bacterial specificity in 16S rRNA sequencing. The optimum solution to prevent bias and to obtain a comprehensive view of complex bacterial communities would be to sequence the entire 16S rRNA gene; however, this is not possible with second generation standard library design and short-read next-generation sequencing technology.

Methods

This paper examines a new process using seven hypervariable or V regions of the 16S rRNA (six amplicons: V2, V3, V4, V6-7, V8, and V9) processed simultaneously on the Ion Torrent Personal Genome Machine (Life Technologies, Grand Island, NY). Four mock samples were amplified using the 16S Ion Metagenomics Kit^™ (Life Technologies) and their sequencing data is subjected to a novel analytical pipeline.

Results

Results are presented at family and genus level. The Kullback-Leibler divergence (D_KL), a measure of the departure of the computed from the nominal bacterial distribution in the mock samples, was used to infer which region performed best at the family and genus levels. Three different hypervariable regions, V2, V4, and V6-7, produced the lowest divergence compared to the known mock sample. The V9 region gave the highest (worst) average D_KL while the V4 gave the lowest (best) average D_KL. In addition to having a high D_KL, the V9 region in both the forward and reverse directions performed the worst finding only 17% and 53% of the known family level and 12% and 47% of the genus level bacteria, while results from the forward and reverse V4 region identified all 17 family level bacteria.

Conclusions

The results of our analysis have shown that our sequencing methods using 6 hypervariable regions of the 16S rRNA and subsequent analysis is valid. This method also allowed for the assessment of how well each of the variable regions might perform simultaneously. Our findings will provide the basis for future work intended to assess microbial abundance at different time points throughout a clinical protocol.

Response of Soil Properties and Microbial Communities to Agriculture: Implications for Primary Productivity and Soil Health Indicators

Agricultural intensification is placing tremendous pressure on the soil's capacity to maintain its functions leading to large-scale ecosystem degradation and loss of productivity in the long term. Therefore, there is an urgent need to find early indicators of soil health degradation in response to agricultural management. In recent years, major advances in soil meta-genomic and spatial studies on microbial communities and community-level molecular characteristics can now be exploited as 'biomarker' indicators of ecosystem processes for monitoring and managing sustainable soil health under global change. However, a continental scale, cross biome approach assessing soil microbial communities and their functional potential to identify the unifying principles governing the susceptibility of soil biodiversity to land conversion is lacking. We conducted a meta-analysis from a dataset generated from 102 peer-reviewed publications as well as unpublished data to explore how properties directly linked to soil nutritional health (total C and N; C:N ratio), primary productivity (NPP) and microbial diversity and composition (relative abundance of major bacterial phyla determined by next generation sequencing techniques) are affected in response to agricultural management across the main biomes of Earth (arid, continental, temperate and tropical). In our analysis, we found strong statistical trends in the relative abundance of several bacterial phyla in agricultural (e.g., Actinobacteria and Chloroflexi) and natural (Acidobacteria, Proteobacteria, and Cyanobacteria) systems across all regions and these trends correlated well with many soil properties. However, main effects of agriculture on soil properties and productivity were biome-dependent. Our meta-analysis provides evidence on the predictable nature of the microbial community responses to vegetation type. This knowledge can be exploited in future for developing a new set of indicators for primary productivity and soil health.

Primer and platform effects on 16S rRNA tag sequencing

Sequencing of 16S rRNA gene tags is a popular method for profiling and comparing microbial communities. The protocols and methods used, however, vary considerably with regard to amplification primers, sequencing primers, sequencing technologies; as well as quality filtering and clustering. How results are affected by these choices, and whether data produced with different protocols can be meaningfully compared, is often unknown. Here we compare results obtained using three different amplification primer sets (targeting V4, V6–V8, and V7–V8) and two sequencing technologies (454 pyrosequencing and Illumina MiSeq) using DNA from a mock community containing a known number of species as well as complex environmental samples whose PCR-independent profiles were estimated using shotgun sequencing. We find that paired-end MiSeq reads produce higher quality data and enabled the use of more aggressive quality control parameters over 454, resulting in a higher retention rate of high quality reads for downstream data analysis. While primer choice considerably influences quantitative abundance estimations, sequencing platform has relatively minor effects when matched primers are used. Beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.

Sputum Bacterial and Fungal Dynamics during Exacerbations of Severe COPD

The changes in the microbial community structure during acute exacerbations of severe chronic obstructive pulmonary disease (COPD) in hospitalized patients remain largely uncharacterized. Therefore, further studies focused on the temporal dynamics and structure of sputum microbial communities during acute exacerbation of COPD (AECOPD) would still be necessary. In our study, the use of molecular microbiological techniques provided insight into both fungal and bacterial diversities in AECOPD patients during hospitalization. In particular, we examined the structure and varieties of lung microbial community in 6 patients with severe AECOPD by amplifying 16S rRNA V4 hyper-variable and internal transcribed spacer (ITS) DNA regions using barcoded primers and the Illumina sequencing platform. Sequence analysis showed 261 bacterial genera representing 20 distinct phyla, with an average number of genera per patient of >157, indicating high diversity. Acinetobacter, Prevotella, Neisseria, Rothia, Lactobacillus, Leptotrichia, Streptococcus, Veillonella, and Actinomyces were the most commonly identified genera, and the average total sequencing number per sputum sample was >10000 18S ITS sequences. The fungal population was typically dominated by Candia, Phialosimplex, Aspergillus, Penicillium, Cladosporium and Eutypella. Our findings highlight that COPD patients have personalized structures and varieties in sputum microbial community during hospitalization periods.

Spatial scales of bacterial community diversity at cold seeps (Eastern Mediterranean Sea)

Cold seeps are highly productive, fragmented marine ecosystems that form at the seafloor around hydrocarbon emission pathways. The products of microbial utilization of methane and other hydrocarbons fuel rich chemosynthetic communities at these sites, with much higher respiration rates compared with the surrounding deep-sea floor. Yet little is known as to the richness, composition and spatial scaling of bacterial communities of cold seeps compared with non-seep communities. Here we assessed the bacterial diversity across nine different cold seeps in the Eastern Mediterranean deep-sea and surrounding seafloor areas. Community similarity analyses were carried out based on automated ribosomal intergenic spacer analysis (ARISA) fingerprinting and high-throughput 454 tag sequencing and were combined with in situ and ex situ geochemical analyses across spatial scales of a few tens of meters to hundreds of kilometers. Seep communities were dominated by Deltaproteobacteria, Epsilonproteobacteria and Gammaproteobacteria and shared, on average, 36% of bacterial types (ARISA OTUs (operational taxonomic units)) with communities from nearby non-seep deep-sea sediments. Bacterial communities of seeps were significantly different from those of non-seep sediments. Within cold seep regions on spatial scales of only tens to hundreds of meters, the bacterial communities differed considerably, sharing <50% of types at the ARISA OTU level. Their variations reflected differences in porewater sulfide concentrations from anaerobic degradation of hydrocarbons. This study shows that cold seep ecosystems contribute substantially to the microbial diversity of the deep-sea.

Microbial diversity in hummock and hollow soils of three wetlands on the Qinghai-Tibetan Plateau revealed by 16S rRNA pyrosequencing

The wetlands of the Qinghai-Tibetan Plateau are believed to play an important role in global nutrient cycling, but the composition and diversity of microorganisms in this ecosystem are poorly characterized. An understanding of the effects of geography and microtopography on microbial populations will provide clues to the underlying mechanisms that structure microbial communities. In this study, we used pyrosequencing-based analysis of 16S rRNA gene sequences to assess and compare the composition of soil microbial communities present in hummock and hollow soils from three wetlands (Dangxiong, Hongyuan and Maduo) on the Qinghai-Tibetan Plateau, the world's highest plateau. A total of 36 bacterial phyla were detected. Proteobacteria (34.5% average relative abundance), Actinobacteria (17.3%) and Bacteroidetes (11%) had the highest relative abundances across all sites. Chloroflexi, Acidobacteria, Verrucomicrobia, Firmicutes, and Planctomycetes were also relatively abundant (1-10%). In addition, archaeal sequences belonging to Euryarchaea, Crenarchaea and Thaumarchaea were detected. Alphaproteobacteria sequences, especially of the order Rhodospirillales, were significantly more abundant in Maduo than Hongyuan and Dangxiong wetlands. Compared with Hongyuan soils, Dangxiong and Maduo had significantly higher relative abundances of Gammaproteobacteria sequences (mainly order Xanthomonadales). Hongyuan wetland had a relatively high abundance of methanogens (mainly genera Methanobacterium, Methanosarcina and Methanosaeta) and methanotrophs (mainly Methylocystis) compared with the other two wetlands. Principal coordinate analysis (PCoA) indicated that the microbial community structure differed between locations and microtopographies and canonical correspondence analysis indicated an association between microbial community structure and soil properties or geography. These insights into the microbial community structure and the main controlling factors in wetlands of the Qinghai-Tibetan Plateau provide a valuable background for further studies on biogeochemical processes in this distinct ecosystem.