Characterization of the bacterial microbiome of Swedish ticks through 16S rRNA amplicon sequencing of whole ticks and of individual tick organs

BACKGROUND

The composition of the microbial flora associated with ixodid ticks has been studied in several species, revealing the importance of geographical origin, developmental stage(s) and feeding status of the tick, as well as substantial differences between tissues and organs. Studying the microbiome in the correct context and scale is therefore necessary for understanding the interactions between tick-borne pathogens and other microorganisms as well as other aspects of tick biology.

METHODS

In the present study the microbial flora of whole Ixodes ricinus, I. persulcatus and I. trianguliceps ticks were analyzed with 16S rRNA amplicon sequencing. Additionally, tick organs (midguts, Malpighian tubules, ovaries, salivary glands) from flat and engorged I. ricinus female ticks were examined with the same methodology.

RESULTS

The most abundant bacteria belonged to the group of Proteobacteria (Cand. Midichloria mitochondrii and Cand. Lariskella). 16S amplicon sequencing of dissected tick organs provided more information on the diversity of I. ricinus-associated microbial flora, especially when organs were collected from engorged ticks. Bacterial genera significantly associated with tick feeding status as well as genera associated with the presence of tick-borne pathogens were identified.

CONCLUSIONS

These results contribute to the knowledge of microbial flora associated with ixodid ticks in their northernmost distribution limit in Europe and opens new perspectives for other investigations on the function of these bacteria, including those using other approaches like in vitro cultivation and in vitro models.

Pyrosequencing and phenotypic microarray to decipher bacterial community variation in Sorghum bicolor (L.) Moench rhizosphere

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Different cultivation practices and climatic conditions play an important role in governing and modulating soil microbial communities.

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This work, investigated the changes in bacterial community composition at taxonomic and functional level in rhizosphere soil of sweet sorghum under extensive cultivation practices at three different field sites of South Africa.

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16S rRNA amplicon sequencing data revealed that at the phylum level, the dominant group was Cyanobacteria with a relative abundance of 63.3%, 71.8% and 81.6% from ASHSOIL1, ASHSOIL2, and ASHSOIL3, respectively.

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Community-level physiological profiling (CLPP) analysis revealed that the metabolic activity of the bacterial community in ASHSOIL3 was the highest, followed by ASHSOIL1 and ASHSOIL2.

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Overall, this study showed that soil pH, nutrient availability and cultivation practices played significant roles in governing the bacterial community composition in sorghum rhizosphere.

Different cultivation practices and climatic conditions play an important role in governing and modulating soil microbial communities as well as soil health. This study investigated, for the first time, keystone microbial taxa inhabiting the rhizosphere of sweet sorghum (Sorghum bicolor) under extensive cultivation practices at three different field sites of South Africa (North West-South (ASHSOIL1); Mpumalanga-West – (ASHSOIL2); and Free State-North West – (ASHSOIL3)). Soil analysis of these sites revealed differences in P, K, Mg, and pH. 16S rRNA amplicon sequencing data revealed that the rhizosphere bacterial microbiome differed significantly both in the structure and composition across the samples. The sequencing data revealed that at the phylum level, the dominant group was Cyanobacteria with a relative abundance of 63.3%, 71.8%, and 81.6% from ASHSOIL1, ASHSOIL2, and ASHSOIL3, respectively. Putative metabolic requirements analyzed by METAGENassist software revealed the ASHSOIL1 sample as the prominent ammonia degrader (21.1%), followed by ASHSOIL3 (17.3%) and ASHSOIL2 (11.1%). The majority of core-microbiome taxa were found to be from Cyanobacteria, Bacteroidetes, and Proteobacteria. Functionally, community-level physiological profiling (CLPP) analysis revealed that the metabolic activity of the bacterial community in ASHSOIL3 was the highest, followed by ASHSOIL1 and ASHSOIL2. This study showed that soil pH and nutrient availability and cultivation practices played significant roles in governing the bacterial community composition in the sorghum rhizosphere across the different sites.

Community profiling focus group: An empowering tool for immigrant community groups

Community psychology profiling, a complex and lengthy intervention methodology, can play an important role in enhancing social cohesion and integrating immigrants into local communities. In this pilot research intervention, we wanted to investigate if the Community Profiling Focus Group, which is flexible and a less time-consuming methodology could be employed to initiate empowering processes in marginalized community groups such as immigrants. Five focus groups were carried out with different immigrants. Overall our research shows that, though immigrants had deep concerns mostly on work issues and low acceptance of foreigners, participating in the Community Profiling Focus Group enabled them to be more proactive and to identify objectives they could reach jointly to increase their empowerment and integration in their communities.

Mechanistic strategies of microbial communities regulating lignocellulose deconstruction in a UK salt marsh

BACKGROUND

Salt marshes are major natural repositories of sequestered organic carbon with high burial rates of organic matter, produced by highly productive native flora. Accumulated carbon predominantly exists as lignocellulose which is metabolised by communities of functionally diverse microbes. However, the organisms that orchestrate this process and the enzymatic mechanisms employed that regulate the accumulation, composition and permanence of this carbon stock are not yet known. We applied meta-exo-proteome proteomics and 16S rRNA gene profiling to study lignocellulose decomposition in situ within the surface level sediments of a natural established UK salt marsh.

RESULTS

Our studies revealed a community dominated by Gammaproteobacteria, Bacteroidetes and Deltaproteobacteria that drive lignocellulose degradation in the salt marsh. We identify 42 families of lignocellulolytic bacteria of which the most active secretors of carbohydrate-active enzymes were observed to be Prolixibacteracea, Flavobacteriaceae, Cellvibrionaceae, Saccharospirillaceae, Alteromonadaceae, Vibrionaceae and Cytophagaceae. These families secreted lignocellulose-active glycoside hydrolase (GH) family enzymes GH3, GH5, GH6, GH9, GH10, GH11, GH13 and GH43 that were associated with degrading Spartina biomass. While fungi were present, we did not detect a lignocellulolytic contribution from fungi which are major contributors to terrestrial lignocellulose deconstruction. Oxidative enzymes such as laccases, peroxidases and lytic polysaccharide monooxygenases that are important for lignocellulose degradation in the terrestrial environment were present but not abundant, while a notable abundance of putative esterases (such as carbohydrate esterase family 1) associated with decoupling lignin from polysaccharides in lignocellulose was observed.

CONCLUSIONS

Here, we identify a diverse cohort of previously undefined bacteria that drive lignocellulose degradation in the surface sediments of the salt marsh environment and describe the enzymatic mechanisms they employ to facilitate this process. Our results increase the understanding of the microbial and molecular mechanisms that underpin carbon sequestration from lignocellulose within salt marsh surface sediments in situ and provide insights into the potential enzymatic mechanisms regulating the enrichment of polyphenolics in salt marsh sediments. Video Abstract.

Utilization of multiple microbial tools to evaluate efficacy of restoration strategies to improve recreational water quality at a Lake Michigan Beach (Racine, WI)

Hydro-meteorological conditions facilitate transport of fecal indicator bacteria (FIB) to the nearshore environment, affecting recreational water quality. North Beach (Racine, Wisconsin, United States), is an exemplar public beach site along Lake Michigan, where precipitation-mediated surface runoff, wave encroachment, stormwater and tributary outflow were demonstrated to contribute to beach advisories. Multiple restoration actions, including installation of a stormwater retention wetland, were successfully deployed to improve recreational water quality. Implementation of molecular methods (e.g. human microbial source tracking markers and Escherichia coli (E. coli) qPCR) assisted in identifying potential pollution sources and improving public health response time. However, periodic water quality failures still occur. As local beach managers reassess restoration measures in response to climatic changes, use of expanded microbial methods (including bacterial community profiling) may contribute to a better understanding of these dynamic environments. In this 2-year study (2015 and 2019), nearshore/offshore Lake Michigan, stormwater, and tributary samples were collected to determine if, 1) the constructed wetland (~50 m from the shoreline) continued to provide stormwater separation/retention and 2) mixing between onshore sources, Root River and Lake Michigan, was increasing due to rising precipitation/lake levels. Monthly rainfall totals were 1.5× higher in 2019 than 2015, coinciding with a 0.63 m lake-level rise. The prevalence of more intense, onshore winds also increased, facilitating interaction between potential reservoirs of FIB with nearshore water through wind driven waves and lake intrusion, e.g. beach sands and the adjacent Root River. While a strong relationship existed between wet weather wetland and North Beach nearshore E. coli concentrations (all sites), bacterial communities were strikingly different. Conversely, bacterial community overlap existed between the Root River mouth and nearshore/offshore sites. These results suggest the constructed wetland can accommodate the climate-related changes observed in this study. Future restoration activities could be directed towards upstream tributary sources in order to minimize microbial contaminants entering Lake Michigan.

MiCoP: microbial community profiling method for detecting viral and fungal organisms in metagenomic samples

Background

High throughput sequencing has spurred the development of metagenomics, which involves the direct analysis of microbial communities in various environments such as soil, ocean water, and the human body. Many existing methods based on marker genes or k-mers have limited sensitivity or are too computationally demanding for many users. Additionally, most work in metagenomics has focused on bacteria and archaea, neglecting to study other key microbes such as viruses and eukaryotes.

Results

Here we present a method, MiCoP (Microbiome Community Profiling), that uses fast-mapping of reads to build a comprehensive reference database of full genomes from viruses and eukaryotes to achieve maximum read usage and enable the analysis of the virome and eukaryome in each sample. We demonstrate that mapping of metagenomic reads is feasible for the smaller viral and eukaryotic reference databases. We show that our method is accurate on simulated and mock community data and identifies many more viral and fungal species than previously-reported results on real data from the Human Microbiome Project.

Conclusions

MiCoP is a mapping-based method that proves more effective than existing methods at abundance profiling of viruses and eukaryotes in metagenomic samples. MiCoP can be used to detect the full diversity of these communities. The code, data, and documentation are publicly available on GitHub at: https://github.com/smangul1/MiCoP.

Sex differences in the nitrate-nitrite-NO• pathway: Role of oral nitrate-reducing bacteria

Oral reduction of nitrate to nitrite is dependent on the oral microbiome and is the first step of an alternative mammalian pathway to produce nitric oxide in humans. Preliminary evidence suggests important sex differences in this pathway. We prospectively investigated sex-differences following inorganic nitrate supplementation on nitrate/nitrite levels and vascular function, and separately examined sex differences in oral nitrate reduction, and oral microbiota by 16S rRNA profiling. At baseline, females exhibit higher nitrite levels in all biological matrices despite similar nitrate levels to males. Following inorganic nitrate supplementation, plasma nitrite was increased to a significantly greater extent in females than in males and pulse wave velocity was only reduced in females. Females exhibited higher oral bacterial nitrate-reducing activity at baseline and after nitrate supplementation. Despite these differences, there were no differences in the composition of either the total salivary microbiota or those oral taxa with nitrate reductase genes. Our results demonstrate that females have augmented oral nitrate reduction that contributes to higher nitrite levels at baseline and also after inorganic nitrate supplementation, however this was not associated with differences in microbial composition (clinicaltrials.gov: NCT01583803).

Functional association prediction by community profiling

Recent years have witnessed unprecedented accumulation of DNA sequences and therefore protein sequences (predicted from DNA sequences), due to the advances of sequencing technology. One of the major sources of the hypothetical proteins is the metagenomics research. Current annotation of metagenomes (collections of short metagenomic sequences or assemblies) relies on similarity searches against known gene/protein families, based on which functional profiles of microbial communities can be built. This practice, however, leaves out the hypothetical proteins, which may outnumber the known proteins for many microbial communities. On the other hand, we may ask: what can we gain from the large number of metagenomes made available by the metagenomic studies, for the annotation of metagenomic sequences as well as functional annotation of hypothetical proteins in general? Here we propose a community profiling approach for predicting functional associations between proteins: two proteins are predicted to be associated if they share similar presence and absence profiles (called community profiles) across microbial communities. Community profiling is conceptually similar to the phylogenetic profiling approach to functional prediction, however with fundamental differences. We tested different profile construction methods, the selection of reference metagenomes, and correlation metrics, among others, to optimize the performance of this new approach. We demonstrated that the community profiling approach alone slightly outperforms the phylogenetic profiling approach for associating proteins in species that are well represented by sequenced genomes, and combining phylogenetic and community profiling further improves (though only marginally) the prediction of functional association. Further we showed that community profiling method significantly outperforms phylogenetic profiling, revealing more functional associations, when applied to a more recently sequenced bacterial genome.

Evidence for polymicrobial communities in explanted vascular filters and atheroma debris

RATIONALE

Microbial communities have been implicated in a variety of disease processes and have been intermittently observed in arterial disease; however, no comprehensive unbiased community analysis has been performed. We hypothesize that complex microbial communities may be involved in chronic vascular diseases as well and may be effectively characterized by molecular assays.

OBJECTIVE

The main objective is to survey vascular debris, atheroma, and vascular filters for polymicrobial communities consisting of prokaryotic and eukaryotic microbes, specifically eukaryotic microbes.

METHODS AND RESULTS

We examined vascular aspirates of atheromatous debris or embolic protection filters in addition to matched peripheral blood samples, from fifteen patients, as well as three cadaveric coronary arteries from two separate patients, for microbial communities. General fluorescence microscopy by Höechst and ethidium bromide DNA stains, prokaryotic and eukaryotic community analysis by Next Generation DNA Sequencing (NGS), and a eukaryotic microbial 9 probe multiplexed quantitative PCR were used to detect and characterize the presence of putative polymicrobial communities. No prokaryotes were detected in peripheral blood; however, in 4 of 9 sequenced filters and in 2 of 7 sequenced atheroma debris samples, prokaryotic populations were identified. By DNA sequencing, eukaryotic microbes were detected in 4 of 15 blood samples, 5 of the 9 sequenced filters, and 3 of the 7 atheroma debris samples. The quantitative multiplex PCR detected sequences consistent with eukaryotic microbes in all 9 analyzed filter samples as well as 5 of the 7 atheroma debris samples. Microscopy reveals putative polymicrobial communities within filters and atheroma debris. The main contributing prokaryotic species in atheroma debris suggest a diverse and novel composition. Additionally, Funneliformis mosseae, an arbuscular mycorrhizal fungus in the Glomeraceae family, was detected in the coronary hard plaque from two patients. Well studied biofilm forming bacteria were not detectable in circulating peripheral blood and were not universally present in atheroma or filters. Analyses of the sequenced eukaryotes are consistent with a diverse of array poorly studied environmental eukaryotes. In summary, out of 15 patients, 6 exhibited molecular evidence of prokaryotes and 14 had molecular evidence of eukaryotic and/or polymicrobial communities in vivo, while 2 post-mortem coronary plaque samples displayed evidence of fungi.

CONCLUSION

Prokaryotes are not consistently observed in atheroma debris or filter samples; however, detection of protozoa and fungi in these samples suggests that they may play a role in arterial vascular disease or atheroma formation.

Source tracking using microbial community fingerprints: Method comparison with hydrodynamic modelling

Urban estuaries around the world are experiencing contamination from diffuse and point sources, which increases risks to public health. To mitigate and manage risks posed by elevated levels of contamination in urban waterways, it is critical to identify the primary water sources of contamination within catchments. Source tracking using microbial community fingerprints is one tool that can be used to identify sources. However, results derived from this approach have not yet been evaluated using independent datasets. As such, the key objectives of this investigation were: (1) to identify the major sources of water responsible for bacterial loadings within an urban estuary using microbial source tracking (MST) using microbial communities; and (2) to evaluate this method using a 3-dimensional hydrodynamic model. The Yarra River estuary, which flows through the city of Melbourne in South-East Australia was the focus of this study. We found that the water sources contributing to the bacterial community in the Yarra River estuary varied temporally depending on the estuary's hydrodynamic conditions. The water source apportionment determined using microbial community MST correlated to those determined using a 3-dimensional hydrodynamic model of the transport and mixing of a tracer in the estuary. While there were some discrepancies between the two methods, this investigation demonstrated that MST using bacterial community fingerprints can identify the primary water sources of microorganisms in an estuarine environment. As such, with further optimization and improvements, microbial community MST has the potential to become a powerful tool that could be practically applied in the mitigation of contaminated aquatic systems.

Rapid infectious disease identification by next-generation DNA sequencing

Currently, there is a critical need to rapidly identify infectious organisms in clinical samples. Next-Generation Sequencing (NGS) could surmount the deficiencies of culture-based methods; however, there are no standardized, automated programs to process NGS data. To address this deficiency, we developed the Rapid Infectious Disease Identification (RIDI™) system. The system requires minimal guidance, which reduces operator errors. The system is compatible with the three major NGS platforms. It automatically interfaces with the sequencing system, detects their data format, configures the analysis type, applies appropriate quality control, and analyzes the results. Sequence information is characterized using both the NCBI database and RIDI™ specific databases. RIDI™ was designed to identify high probability sequence matches and more divergent matches that could represent different or novel species. We challenged the system using defined American Type Culture Collection (ATCC) reference standards of 27 species, both individually and in varying combinations. The system was able to rapidly detect known organisms in <12h with multi-sample throughput. The system accurately identifies 99.5% of the DNA sequence reads at the genus-level and 75.3% at the species-level in reference standards. It has a limit of detection of 146cells/ml in simulated clinical samples, and is also able to identify the components of polymicrobial samples with 16.9% discrepancy at the genus-level and 31.2% at the species-level. Thus, the system's effectiveness may exceed current methods, especially in situations where culture methods could produce false negatives or where rapid results would influence patient outcomes.

Two amplicon sequencing strategies revealed different facets of the prokaryotic community associated with the anaerobic treatment of vinasses from ethanol distilleries

The prokaryotic consortium from a pilot-scale UASB reactor fed with vinasses from ethanol distilleries was evaluated by means of amplicon sequencing of the 16S rRNA gene. Two different sets of primers targeted to overlapping regions of the V4-16S region were used to gain a broad picture of such community and to perform a comparative analysis. From the two datasets obtained, prevalent phyla were Firmicutes, Verrucomicrobia and Thermotogae. Interestingly, one set of primers captured variability in both the bacterial and archaeal portions of the community, whilst the other one revealed a more diverse community structure, but only in the Bacteria domain. Although a certain level of agreement between the two strategies was observed, sharp differences indicate that different facets of the community were disclosed by each approach.