Статті в журналах: "16S rRNA profiling"

1

Nakayama, Jiro. "Pyrosequence-Based 16S rRNA Profiling of Gastro-Intestinal Microbiota." Bioscience and Microflora 29, no. 2 (2010): 83–96. http://dx.doi.org/10.12938/bifidus.29.83.

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2

Cuscó, Anna, Carlotta Catozzi, Joaquim Viñes, Armand Sanchez, and Olga Francino. "Microbiota profiling with long amplicons using Nanopore sequencing: full-length 16S rRNA gene and whole rrn operon." F1000Research 7 (November 6, 2018): 1755. http://dx.doi.org/10.12688/f1000research.16817.1.

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Background: Profiling the microbiome of low-biomass samples is challenging for metagenomics since these samples often contain DNA from other sources, such as the host or the environment. The usual approach is sequencing specific hypervariable regions of the 16S rRNA gene, which fails to assign taxonomy to genus and species level. Here, we aim to assess long-amplicon PCR-based approaches for assigning taxonomy at the genus and species level. We use Nanopore sequencing with two different markers: full-length 16S rRNA (~1,500 bp) and the whole rrn operon (16S rRNA–ITS–23S rRNA; 4,500 bp). Methods: We sequenced a clinical isolate of Staphylococcus pseudintermedius, two mock communities (HM-783D, Bei Resources; D6306, ZymoBIOMICS™) and two pools of low-biomass samples (dog skin from either the chin or dorsal back), using the MinION™ sequencer 1D PCR barcoding kit. Sequences were pre-processed, and data were analyzed using the WIMP workflow on EPI2ME or Minimap2 software with rrn database. Results: The full-length 16S rRNA and the rrn operon were used to retrieve the microbiota composition at the genus and species level from the bacterial isolate, mock communities and complex skin samples. For the Staphylococcus pseudintermedius isolate, when using EPI2ME, the amplicons were assigned to the correct bacterial species in ~98% of the cases with the rrn operon marker, and in ~68% of the cases with the 16S rRNA gene. In both skin microbiota samples, we detected many species with an environmental origin. In chin, we found different Pseudomonas species in high abundance, whereas in dorsal skin there were more taxa with lower abundances. Conclusions: Both full-length 16S rRNA and the rrn operon retrieved the microbiota composition of simple and complex microbial communities, even from the low-biomass samples such as dog skin. For an increased resolution at the species level, using the rrn operon would be the best choice.

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3

Rampelotto, Pabulo H., Aline F. R. Sereia, Luiz Felipe V. de Oliveira, and Rogério Margis. "Exploring the Hospital Microbiome by High-Resolution 16S rRNA Profiling." International Journal of Molecular Sciences 20, no. 12 (June 25, 2019): 3099. http://dx.doi.org/10.3390/ijms20123099.

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The aim of this work was to analyze and compare the bacterial communities of 663 samples from a Brazilian hospital by using high-throughput sequencing of the 16S rRNA gene. To increase taxonomic profiling and specificity of 16S-based identification, a strict sequence quality filtering process was applied for the accurate identification of clinically relevant bacterial taxa. Our results indicate that the hospital environment is predominantly inhabited by closely related species. A massive dominance of a few taxa in all taxonomic levels down to the genera was observed, where the ten most abundant genera in each facility represented 64.4% of all observed taxa, with a major predominance of Acinetobacter and Pseudomonas. The presence of several nosocomial pathogens was revealed. Co-occurrence analysis indicated that the present hospital microbial network had low connectedness, forming a clustered topology, but not structured among groups of nodes (i.e., modules). Furthermore, we were able to detect ecologically relevant relationships between specific microbial taxa, in particular, potential competition between pathogens and non-pathogens. Overall, these results provide new insight into different aspects of a hospital microbiome and indicate that 16S rRNA sequencing may serve as a robust one-step tool for microbiological identification and characterization of a wide range of clinically relevant bacterial taxa in hospital settings with a high resolution.

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4

Kim, Hyojung, Sora Kim, and Sungwon Jung. "Instruction of microbiome taxonomic profiling based on 16S rRNA sequencing." Journal of Microbiology 58, no. 3 (February 27, 2020): 193–205. http://dx.doi.org/10.1007/s12275-020-9556-y.

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5

Cuscó, Anna, Carlotta Catozzi, Joaquim Viñes, Armand Sanchez, and Olga Francino. "Microbiota profiling with long amplicons using Nanopore sequencing: full-length 16S rRNA gene and the 16S-ITS-23S of the rrn operon." F1000Research 7 (August 1, 2019): 1755. http://dx.doi.org/10.12688/f1000research.16817.2.

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Background: Profiling the microbiome of low-biomass samples is challenging for metagenomics since these samples are prone to contain DNA from other sources (e.g. host or environment). The usual approach is sequencing short regions of the 16S rRNA gene, which fails to assign taxonomy to genus and species level. To achieve an increased taxonomic resolution, we aim to develop long-amplicon PCR-based approaches using Nanopore sequencing. We assessed two different genetic markers: the full-length 16S rRNA (~1,500 bp) and the 16S-ITS-23S region from the rrn operon (4,300 bp). Methods: We sequenced a clinical isolate of Staphylococcus pseudintermedius, two mock communities and two pools of low-biomass samples (dog skin). Nanopore sequencing was performed on MinION™ using the 1D PCR barcoding kit. Sequences were pre-processed, and data were analyzed using EPI2ME or Minimap2 with rrn database. Consensus sequences of the 16S-ITS-23S genetic marker were obtained using canu. Results: The full-length 16S rRNA and the 16S-ITS-23S region of the rrn operon were used to retrieve the microbiota composition of the samples at the genus and species level. For the Staphylococcus pseudintermedius isolate, the amplicons were assigned to the correct bacterial species in ~98% of the cases with the16S-ITS-23S genetic marker, and in ~68%, with the 16S rRNA gene when using EPI2ME. Using mock communities, we found that the full-length 16S rRNA gene represented better the abundances of a microbial community; whereas, 16S-ITS-23S obtained better resolution at the species level. Finally, we characterized low-biomass skin microbiota samples and detected species with an environmental origin. Conclusions: Both full-length 16S rRNA and the 16S-ITS-23S of the rrn operon retrieved the microbiota composition of simple and complex microbial communities, even from the low-biomass samples such as dog skin. For an increased resolution at the species level, targeting the 16S-ITS-23S of the rrn operon would be the best choice.

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6

Hiibel, Sage R., Amy Pruden, Barbara Crimi, and Kenneth F. Reardon. "Active community profiling via capillary electrophoresis single-strand conformation polymorphism analysis of amplified 16S rRNA and 16S rRNA genes." Journal of Microbiological Methods 83, no. 3 (December 2010): 286–90. http://dx.doi.org/10.1016/j.mimet.2010.10.002.

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7

Sulaiman, Imran, Benjamin G. Wu, Yonghua Li, Jun-Chieh Tsay, Maya Sauthoff, Adrienne S. Scott, Kun Ji, et al. "Functional lower airways genomic profiling of the microbiome to capture active microbial metabolism." European Respiratory Journal 58, no. 1 (January 14, 2021): 2003434. http://dx.doi.org/10.1183/13993003.03434-2020.

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BackgroundMicrobiome studies of the lower airways based on bacterial 16S rRNA gene sequencing assess microbial community structure but can only infer functional characteristics. Microbial products, such as short-chain fatty acids (SCFAs), in the lower airways have significant impact on the host's immune tone. Thus, functional approaches to the analyses of the microbiome are necessary.MethodsHere we used upper and lower airway samples from a research bronchoscopy smoker cohort. In addition, we validated our results in an experimental mouse model. We extended our microbiota characterisation beyond 16S rRNA gene sequencing with the use of whole-genome shotgun (WGS) and RNA metatranscriptome sequencing. SCFAs were also measured in lower airway samples and correlated with each of the sequencing datasets. In the mouse model, 16S rRNA gene and RNA metatranscriptome sequencing were performed.ResultsFunctional evaluations of the lower airway microbiota using inferred metagenome, WGS and metatranscriptome data were dissimilar. Comparison with measured levels of SCFAs shows that the inferred metagenome from the 16S rRNA gene sequencing data was poorly correlated, while better correlations were noted when SCFA levels were compared with WGS and metatranscriptome data. Modelling lower airway aspiration with oral commensals in a mouse model showed that the metatranscriptome most efficiently captures transient active microbial metabolism, which was overestimated by 16S rRNA gene sequencing.ConclusionsFunctional characterisation of the lower airway microbiota through metatranscriptome data identifies metabolically active organisms capable of producing metabolites with immunomodulatory capacity, such as SCFAs.

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8

Gu, F., Y. Li, C. Zhou, D. T. W. Wong, C. M. Ho, F. Qi, and W. Shi. "Bacterial 16S rRNA/rDNA Profiling in the Liquid Phase of Human Saliva." Open Dentistry Journal 3, no. 1 (April 28, 2009): 80–84. http://dx.doi.org/10.2174/1874210600903010080.

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Human saliva can be separated by centrifugation into cell pellet and cell-free supernatant, which are called cellular phase and liquid phase in this study. While it is well documented that the cellular phase of saliva contains hundreds of oral bacteria species, little is known whether the liquid phase of saliva contains any information related to oral microbiota. In this study, we analyzed the bacterial nucleic acid contents of the liquid phase of saliva. Using primers universal to most eubacterial 16S rDNA, we detected large amounts of bacterial 16S rRNA and rDNA in the cell-free phase of saliva. Random sequencing analysis of forty PCR amplicons from the cell-free phase of saliva led to 15 operational taxonomic unit (OTU) groups. Furthermore, using denaturing gradient gel electrophoresis (DGGE), we compared 16S rRNA/rDNA profiles derived from liquid phases and cellular phases of saliva samples, and found positive correlations (Pearson Correlation=0.822,P<0.001) between these sample groups. These findings indicate that the liquid phase of saliva contains numerous bacterial 16S rRNA/rDNA molecules that have correlations with bacteria existing in the cellular phase.

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9

Wade, W. G., and E. M. Prosdocimi. "Profiling of Oral Bacterial Communities." Journal of Dental Research 99, no. 6 (April 14, 2020): 621–29. http://dx.doi.org/10.1177/0022034520914594.

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The profiling of bacterial communities by the sequencing of housekeeping genes such as that encoding the small subunit ribosomal RNA has revealed the extensive diversity of bacterial life on earth. Standard protocols have been developed and are widely used for this application, but individual habitats may require modification of methods. This review discusses the sequencing and analysis methods most appropriate for the study of the bacterial component of the human oral microbiota. If possible, DNA should be extracted from samples soon after collection. If samples have to be stored for practical reasons, precautions to avoid DNA degradation on freezing should be taken. A critical aspect of profiling oral bacterial communities is the choice of region of the 16S rRNA gene for sequencing. The V1-V2 region provides the best discrimination between species of the genus Streptococcus, the most common genus in the mouth and important in health and disease. The MiSeq platform is most commonly used for sequencing, but long-read technologies are now becoming available that should improve the resolution of analyses. There are a variety of well-established data analysis pipelines available, including mothur and QIIME, which identify sequence reads as phylotypes by comparing them to reference data sets or grouping them into operational taxonomic units. DADA2 has improved sequence error correction capabilities and resolves reads to unique variants. Two curated oral 16S rRNA databases are available: HOMD and CORE. Expert interpretation of community profiles is required, both to detect the presence of contaminating DNA, which is commonly present in the reagents used in analysis, and to differentiate oral and nonoral bacteria and determine the significance of findings. Despite advances in shotgun whole-genome metagenomic methods, oral bacterial community profiling via 16S rRNA sequence analysis remains a valuable technique for the characterization of oral bacterial populations.

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10

van den Bogert, Bartholomeus, Willem M. de Vos, Erwin G. Zoetendal, and Michiel Kleerebezem. "Microarray Analysis and Barcoded Pyrosequencing Provide Consistent Microbial Profiles Depending on the Source of Human Intestinal Samples." Applied and Environmental Microbiology 77, no. 6 (January 21, 2011): 2071–80. http://dx.doi.org/10.1128/aem.02477-10.

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ABSTRACTLarge-scale and in-depth characterization of the intestinal microbiota necessitates application of high-throughput 16S rRNA gene-based technologies, such as barcoded pyrosequencing and phylogenetic microarray analysis. In this study, the two techniques were compared and contrasted for analysis of the bacterial composition in three fecal and three small intestinal samples from human individuals. As PCR remains a crucial step in sample preparation for both techniques, different forward primers were used for amplification to assess their impact on microbial profiling results. An average of 7,944 pyrosequences, spanning the V1 and V2 region of 16S rRNA genes, was obtained per sample. Although primer choice in barcoded pyrosequencing did not affect species richness and diversity estimates, detection ofActinobacteriastrongly depended on the selected primer. Microbial profiles obtained by pyrosequencing and phylogenetic microarray analysis (HITChip) correlated strongly for fecal and ileal lumen samples but were less concordant for ileostomy effluent. Quantitative PCR was employed to investigate the deviations in profiling between pyrosequencing and HITChip analysis. Since cloning and sequencing of random 16S rRNA genes from ileostomy effluent confirmed the presence of novel intestinal phylotypes detected by pyrosequencing, especially those belonging to theVeillonellagroup, the divergence between pyrosequencing and the HITChip is likely due to the relatively low number of available 16S rRNA gene sequences of small intestinal origin in the DNA databases that were used for HITChip probe design. Overall, this study demonstrated that equivalent biological conclusions are obtained by high-throughput profiling of microbial communities, independent of technology or primer choice.

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Mancabelli, Leonardo, Christian Milani, Gabriele Andrea Lugli, Federico Fontana, Francesca Turroni, Douwe van Sinderen, and Marco Ventura. "The Impact of Primer Design on Amplicon-Based Metagenomic Profiling Accuracy: Detailed Insights into Bifidobacterial Community Structure." Microorganisms 8, no. 1 (January 17, 2020): 131. http://dx.doi.org/10.3390/microorganisms8010131.

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Next Generation Sequencing (NGS) technologies have overcome the limitations of cultivation-dependent approaches and allowed detailed study of bacterial populations that inhabit the human body. The consortium of bacteria residing in the human intestinal tract, also known as the gut microbiota, impacts several physiological processes important for preservation of the health status of the host. The most widespread microbiota profiling method is based on amplification and sequencing of a variable portion of the 16S rRNA gene as a universal taxonomic marker among members of the Bacteria domain. Despite its popularity and obvious advantages, this 16S rRNA gene-based approach comes with some important limitations. In particular, the choice of the primer pair for amplification plays a major role in defining the accuracy of the reconstructed bacterial profiles. In the current study, we performed an in silico PCR using all currently described 16S rRNA gene-targeting primer pairs (PP) in order to assess their efficiency. Our results show that V3, V4, V5, and V6 were the optimal regions on which to design 16S rRNA metagenomic primers. In detail, PP39 (Probio_Uni/Probio_Rev), PP41 (341F/534R), and PP72 (970F/1050R) were the most suitable primer pairs with an amplification efficiency of >98.5%. Furthermore, the Bifidobacterium genus was examined as a test case for accurate evaluation of intra-genus performances at subspecies level. Intriguingly, the in silico analysis revealed that primer pair PP55 (527f/1406r) was unable to amplify the targeted region of any member of this bacterial genus, while several other primer pairs seem to rather inefficiently amplify the target region of the main bifidobacterial taxa. These results highlight that selection of a 16S rRNA gene-based PP should be done with utmost care in order to avoid biases in microbiota profiling results.

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Girija, D., P. K. Rajeevan, Swathi Balakrishnan, P. S. Panchami, and Mahesh Mohan. "16S rRNA gene taxonomic profiling of endophytic bacteria associated with phylaenopsis roots." Journal of Horticultural Sciences 13, no. 1 (June 30, 2018): 103–7. http://dx.doi.org/10.24154/jhs.2018.v13i01.012.

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Orchids are one of the main groups of ornamental plants commercially exploited. In the present study, we analyzed the diversity of bacterial community in Phalaenopsis root using metagenomic approach. The diversity of bacterial taxonomic category was assessed at different Operational Taxonomic Unit (OTU) levels using Ribosomal Database Project (RDP) pipeline and MG-RAST. At phylum level, Proteobacteria (61.34%) was the most dominant group followed by unclassified derived from bacteria (24.74%) and Actinobacteria (12.52%). Genus level analysis revealed the abundance of Rubrobacter, Pseudomonas and Acinetobacter. The study revealed that of the total species detected 50.83 per cent were unclassified, stressing the importance of metagenomics to assess the diversity of endophytes associated with orchid roots.

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13

Kim, J. Y., M. H. Yi, Y. Hwang, J. Y. Lee, I. Y. Lee, D. Yong, and T. S. Yong. "16S rRNA profiling of the Dermatophagoides farinae core microbiome: Enterococcus and Bartonella." Clinical & Experimental Allergy 48, no. 5 (March 25, 2018): 607–10. http://dx.doi.org/10.1111/cea.13104.

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14

Langille, Morgan G. I., Jesse Zaneveld, J. Gregory Caporaso, Daniel McDonald, Dan Knights, Joshua A. Reyes, Jose C. Clemente, et al. "Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences." Nature Biotechnology 31, no. 9 (August 25, 2013): 814–21. http://dx.doi.org/10.1038/nbt.2676.

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15

Merkel, A. Yu, I. Yu Tarnovetskii, O. A. Podosokorskaya, and S. V. Toshchakov. "Analysis of 16S rRNA Primer Systems for Profiling of Thermophilic Microbial Communities." Microbiology 88, no. 6 (November 2019): 671–80. http://dx.doi.org/10.1134/s0026261719060110.

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16

Gupta, Ayushi, and Suresh Nair. "Pseudomonas-specific 16S rRNA insect gut-microbiome profiling using next-generation sequencing." STAR Protocols 4, no. 1 (March 2023): 101941. http://dx.doi.org/10.1016/j.xpro.2022.101941.

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17

Bonfantine, Krista L., Stacey M. Trevathan-Tackett, Ty G. Matthews, Ana Neckovic, and Han Ming Gan. "Dumpster diving for diatom plastid 16S rRNA genes." PeerJ 9 (July 1, 2021): e11576. http://dx.doi.org/10.7717/peerj.11576.

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High throughput sequencing is improving the efficiency of monitoring diatoms, which inhabit and support aquatic ecosystems across the globe. In this study, we explored the potential of a standard V4 515F-806RB primer pair in recovering diatom plastid 16S rRNA sequences. We used PhytoREF to classify the 16S reads from our freshwater biofilm field sampling from three stream segments across two streams in south-eastern Australia and retrieved diatom community data from other, publicly deposited, Australian 16S amplicon datasets. When these diatom operational taxonomic units (OTUs) were traced using the default RDPII and NCBI databases, 68% were characterized as uncultured cyanobacteria. We analysed the 16S rRNA sequences from 72 stream biofilm samples, separated the chloroplast OTUs, and classified them using the PhytoREF database. After filtering the reads attributed to Bacillariophyta (relative abundance >1%), 71 diatom OTUs comprising more than 90% of the diatom reads in each stream biofilm sample were identified. Beta-diversity analyses demonstrated significantly different diatom assemblages and discrimination among river segments. To further test the approach, the diatom OTUs from our biofilm sampling were used as reference sequences to identify diatom reads from other Australian 16S rRNA datasets in the NCBI-SRA database. Across the three selected public datasets, 67 of our 71 diatom OTUs were detected in other Australian ecosystems. Our results show that diatom plastid 16S rRNA genes are readily amplified with existing 515F-806RB primer sets. Therefore, the volume of existing 16S rRNA amplicon datasets initially generated for microbial community profiling can also be used to detect, characterize, and map diatom distribution to inform phylogeny and ecological health assessments, and can be extended into a range of ecological and industrial applications. To our knowledge, this study represents the first attempt to classify freshwater samples using this approach and the first application of PhytoREF in Australia.

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18

Liu, B. Y., Z. Y. Wang, H. R. Wang, P. Hu, D. Xu, and Q. Wang. "Molecular profiling of bacterial species in the geese cecum." Czech Journal of Animal Science 56, No. 4 (April 5, 2011): 192–203. http://dx.doi.org/10.17221/1433-cjas.

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The purpose of this study was to analyse the microbial diversity in the caecum of geese using a 16S ribosomal RNA gene (rRNA) clone library approach. A total of 160 clones and 124 clones were sequenced and phylogenetically analysed from the contents and mucosa of the caecum of Yang Zhou geese, respectively. The result indicated that there was a rich variety of bacteria in the caecum contents. Forty-six operational taxonomic units (OTUs) based on a 98% similarity criterion were classified in the contents of goose caecum, as compared to 29 OTUs based on a 97% similarity criterion in the mucosa of goose caecum. The sequences were assigned to 7 and 5 groups in the contents and mucosa of goose caecum, respectively. Contents of goose caecum were dominantly occupied by Clostridia-related species (58.7%) with other abundant sequences being related to Bacteroidetes (26.9%) and Erysipelotrichi (11.2%). Gammaproteobacteria (59.6%) and Clostridia (20.1%) were predominant in the mucosa of goose caecum.

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19

Callahan, Benjamin J., Joan Wong, Cheryl Heiner, Steve Oh, Casey M. Theriot, Ajay S. Gulati, Sarah K. McGill, and Michael K. Dougherty. "High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution." Nucleic Acids Research 47, no. 18 (July 3, 2019): e103-e103. http://dx.doi.org/10.1093/nar/gkz569.

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AbstractTargeted PCR amplification and high-throughput sequencing (amplicon sequencing) of 16S rRNA gene fragments is widely used to profile microbial communities. New long-read sequencing technologies can sequence the entire 16S rRNA gene, but higher error rates have limited their attractiveness when accuracy is important. Here we present a high-throughput amplicon sequencing methodology based on PacBio circular consensus sequencing and the DADA2 sample inference method that measures the full-length 16S rRNA gene with single-nucleotide resolution and a near-zero error rate. In two artificial communities of known composition, our method recovered the full complement of full-length 16S sequence variants from expected community members without residual errors. The measured abundances of intra-genomic sequence variants were in the integral ratios expected from the genuine allelic variants within a genome. The full-length 16S gene sequences recovered by our approach allowed Escherichia coli strains to be correctly classified to the O157:H7 and K12 sub-species clades. In human fecal samples, our method showed strong technical replication and was able to recover the full complement of 16S rRNA alleles in several E. coli strains. There are likely many applications beyond microbial profiling for which high-throughput amplicon sequencing of complete genes with single-nucleotide resolution will be of use.

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20

Zhang, Hui, Xiangdan Yu, Zhe Zhang, Zhenhua Liu, Cong Tang, Kun Zhao, Shiyan Liu, et al. "Nanoliter-scale next-generation sequencing library-mediated high-throughput 16S rRNA microbial community profiling." BioTechniques 68, no. 4 (April 2020): 204–10. http://dx.doi.org/10.2144/btn-2019-0102.

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An ultra-high-throughput workflow for next-generation sequencing library construction at nanoliter scale for amplicon sequencing, termed Smartchip Nanowell Platform for Target Enrichment, was established using a nanodispenser system and a nanoliter-scale PCR chip. To demonstrate its cost and time advantages over conventional methods for library construction, quality control and pooling for large-scale samples, target amplicon sequencing of the 16S ribosomal RNA gene V3-V4 region widely used for microbial community profiling was chosen for comparison. The finding of no significant difference in microbial community profiling between the two methods strongly supports the conclusion that Smartchip Nanowell Platform for Target Enrichment is a cost-effective method for next-generation sequencing library construction for large-scale samples to conduct amplicon sequencing-based applications.

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Lee, Se-Hui, Hye-Jin Ku, Min-Ju Ahn, Ji-Sang Hong, Se Hee Lee, Hakdong Shin, Keun Chul Lee, et al. "Weissella jogaejeotgali sp. nov., isolated from jogae jeotgal, a traditional Korean fermented seafood." International Journal of Systematic and Evolutionary Microbiology 65, Pt_12 (December 1, 2015): 4674–81. http://dx.doi.org/10.1099/ijsem.0.000631.

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Strain FOL01T was isolated from traditionally fermented Korean jogae jeotgal (fermented clams). Phylogenetic sequence analysis of the 16S rRNA gene from FOL01T revealed that it is closely related to Weissella thailandensis FS61-1T and Weissella paramesenteroides ATCC 33313T with 99.39 % and 98.50 % 16S rRNA gene sequence similarities, respectively. API and VITEK analyses showed that strain FOL01T could be separated from its nearest phylogenetic relatives with respect to carbohydrate fermentation and antibiotic resistance. Subsequent amplified rRNA gene restriction analysis of 16S rRNA genes and HaeIII-restriction enzyme profiling of genomic DNAs revealed different band patterns. In addition, DNA–DNA hybridization of genomic DNAs showed 63.9 % relatedness. Analysis of the composition of cellular fatty acids confirmed that strain FOL01T differs from its close relatives and supports the proposal to assign this organism to a novel species of the genus Weissella. Based on these results, strain FOL01T could be classified as a novel species of the genus Weissella, for which the name Weissella jogaejeotgali sp. nov. is proposed. The type strain is FOL01T ( = KCCM 43128T = JCM 30589T).

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22

Oyewusi, Habeebat Adekilekun, Roswanira Abdul Wahab, Mohamed Faraj Edbeib, Mohd Azrul Naim Mohamad, Azzmer Azzar Abdul Hamid, Yilmaz Kaya, and Fahrul Huyop. "Functional profiling of bacterial communities in Lake Tuz using 16S rRNA gene sequences." Biotechnology & Biotechnological Equipment 35, no. 1 (October 31, 2020): 1–10. http://dx.doi.org/10.1080/13102818.2020.1840437.

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23

Limayem, Alya, Andrew Micciche, Bina Nayak, and Shyam Mohapatra. "Prokaryotic community profiling of local algae wastewaters using advanced 16S rRNA gene sequencing." Environmental Science and Pollution Research 25, no. 1 (October 23, 2017): 704–11. http://dx.doi.org/10.1007/s11356-017-0078-z.

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24

Korenori, Yuki, Jiahui Jiang, and Jiro Nakayama. "Current status and problems of 16S rRNA pyrosequencing- based profiling of gastro-intestinal microbiota." Japanese Journal of Lactic Acid Bacteria 23, no. 1 (2012): 24–34. http://dx.doi.org/10.4109/jslab.23.24.

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25

Abundo, Michael E. C., John M. Ngunjiri, Kara J. M. Taylor, Hana Ji, Amir Ghorbani, Mahesh K. C., Bonnie P. Weber, Timothy J. Johnson, and Chang-Won Lee. "Assessment of two DNA extraction kits for profiling poultry respiratory microbiota from multiple sample types." PLOS ONE 16, no. 1 (January 6, 2021): e0241732. http://dx.doi.org/10.1371/journal.pone.0241732.

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Characterization of poultry microbiota is becoming increasingly important due to the growing need for microbiome-based interventions to improve poultry health and production performance. However, the lack of standardized protocols for sampling, sample processing, DNA extraction, sequencing, and bioinformatic analysis can hinder data comparison between studies. Here, we investigated how the DNA extraction process affects microbial community compositions and diversity metrics in different chicken respiratory sample types including choanal and tracheal swabs, nasal cavity and tracheal washes, and lower respiratory lavage. We did a side-by-side comparison of the performances of Qiagen DNeasy blood and tissue (BT) and ZymoBIOMICS DNA Miniprep (ZB) kits. In general, samples extracted with the BT kit yielded higher concentrations of total DNA while those extracted with the ZB kit contained higher numbers of bacterial 16S rRNA gene copies per unit volume. Therefore, the samples were normalized to equal amounts of 16S rRNA gene copies prior to sequencing. For each sample type, all predominant bacterial taxa detected in samples extracted with one kit were present in replicate samples extracted with the other kit and did not show significant differences at the class level. However, a few differentially abundant shared taxa were observed at family and genus levels. Furthermore, between-kit differences in alpha and beta diversity metrics at the amplicon sequence variant level were statistically indistinguishable. Therefore, both kits perform similarly in terms of 16S rRNA gene-based poultry microbiome analysis for the sample types analyzed in this study.

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Wang, Yin, Rudong Li, Yuhua Zhou, Zongxin Ling, Xiaokui Guo, Lu Xie, and Lei Liu. "Motif-Based Text Mining of Microbial Metagenome Redundancy Profiling Data for Disease Classification." BioMed Research International 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/6598307.

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Background. Text data of 16S rRNA are informative for classifications of microbiota-associated diseases. However, the raw text data need to be systematically processed so that features for classification can be defined/extracted; moreover, the high-dimension feature spaces generated by the text data also pose an additional difficulty.Results. Here we present a Phylogenetic Tree-Based Motif Finding algorithm (PMF) to analyze 16S rRNA text data. By integrating phylogenetic rules and other statistical indexes for classification, we can effectively reduce the dimension of the large feature spaces generated by the text datasets. Using the retrieved motifs in combination with common classification methods, we can discriminate different samples of both pneumonia and dental caries better than other existing methods.Conclusions. We extend the phylogenetic approaches to perform supervised learning on microbiota text data to discriminate the pathological states for pneumonia and dental caries. The results have shown that PMF may enhance the efficiency and reliability in analyzing high-dimension text data.

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Ramlal, P. S., J. Lin, C. A. Buckley, T. A. Stenström, I. D. Amoah, M. Okpeku, A. Kanzi, and V. Ramsuran. "16S rRNA-based metagenomic profiling of microbes on contact surfaces within shared sanitation facilities." Ecological Genetics and Genomics 21 (December 2021): 100095. http://dx.doi.org/10.1016/j.egg.2021.100095.

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28

Chen, Wei, Yongmei Cheng, Clarence Zhang, Shaowu Zhang, and Hongyu Zhao. "MSClust: A Multi-Seeds based Clustering algorithm for microbiome profiling using 16S rRNA sequence." Journal of Microbiological Methods 94, no. 3 (September 2013): 347–55. http://dx.doi.org/10.1016/j.mimet.2013.07.004.

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29

De Filippis, Francesca, Eugenio Parente, Teresa Zotta, and Danilo Ercolini. "A comparison of bioinformatic approaches for 16S rRNA gene profiling of food bacterial microbiota." International Journal of Food Microbiology 265 (January 2018): 9–17. http://dx.doi.org/10.1016/j.ijfoodmicro.2017.10.028.

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30

Kim, Minseok, and Zhongtang Yu. "Variations in 16S rRNA-based microbiome profiling between pyrosequencing runs and between pyrosequencing facilities." Journal of Microbiology 52, no. 5 (April 11, 2014): 355–65. http://dx.doi.org/10.1007/s12275-014-3443-3.

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31

Song, Yun Gyu, Sang Gun Shim, Kwang Min Kim, Dong-Hae Lee, Dae-Soo Kim, Sang-Haeng Choi, Jae-Young Song, et al. "Profiling of the bacteria responsible for pyogenic liver abscess by 16S rRNA gene pyrosequencing." Journal of Microbiology 52, no. 6 (May 29, 2014): 504–9. http://dx.doi.org/10.1007/s12275-014-4241-7.

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32

Nold, Stephen C., Joseph B. Pangborn, Heidi A. Zajack, Scott T. Kendall, Richard R. Rediske, and Bopaiah A. Biddanda. "Benthic Bacterial Diversity in Submerged Sinkhole Ecosystems." Applied and Environmental Microbiology 76, no. 1 (October 30, 2009): 347–51. http://dx.doi.org/10.1128/aem.01186-09.

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ABSTRACT Physicochemical characterization, automated ribosomal intergenic spacer analysis (ARISA) community profiling, and 16S rRNA gene sequencing approaches were used to study bacterial communities inhabiting submerged Lake Huron sinkholes inundated with hypoxic, sulfate-rich groundwater. Photosynthetic cyanobacterial mats on the sediment surface were dominated by Phormidium autumnale, while deeper, organically rich sediments contained diverse and active bacterial communities.

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33

Song, Ying, Dongze Lu, Honggang Wang, Zhenyi Zhou, Xian Luo, Manjing Ma, Songze Ke, Hong Wang, Yanlei Yu, and Bin Wei. "Metagenomic Insights into the Anti-Obesity Effect of a Polysaccharide from Saccharina japonica." Foods 12, no. 3 (February 3, 2023): 665. http://dx.doi.org/10.3390/foods12030665.

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Saccharina japonica polysaccharides exhibit great potential to be developed as anti-obesity and prebiotic health products, but the underlying mechanism has not been adequately addressed. In this study, we investigated the potential mechanism of a S. japonica polysaccharide fraction (SjC) in preventing high-fat-diet (HFD)-induced obesity in mice using 16S rRNA gene and shotgun metagenomic sequencing analysis. SjC was characterized as a 756 kDa sulfated polysaccharide and 16 weeks of SjC supplementation significantly alleviated HFD-induced obesity, insulin resistance, and glucose metabolism disorders. The 16S rRNA and metagenomic sequencing analysis demonstrated that SjC supplementation prevented gut microbiota dysbiosis mainly by regulating the relative abundance of Desulfovibrio and Akkermansia. Metagenomic functional profiling demonstrated that SjC treatment predominantly suppressed the amino acid metabolism of gut microbiota. Linking of 16S rRNA genes with metagenome-assembled genomes indicated that SjC enriched at least 22 gut bacterial species with fucoidan-degrading potential including Desulfovibrio and Akkermansia, which showed significant correlations with bodyweight. In conclusion, our results suggest that SjC exhibits a promising potential as an anti-obesity health product and the interaction between SjC and fucoidan-degrading bacteria may be associated with its anti-obesity effect.

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34

Fisunov, G. Yu, D. V. Evsyutina, A. A. Arzamasov, I. O. Butenko, and V. M. Govorun. "Profiling of Mycoplasma gallisepticum Ribosomes." Acta Naturae 7, no. 4 (December 15, 2015): 107–12. http://dx.doi.org/10.32607/20758251-2015-7-4-107-112.

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The development of high-throughput technologies is increasingly resulting in identification of numerous cases of low correlation between mRNA and the protein level in cells. These controversial observations were made on various bacteria, such as E. coli, Desulfovibrio vulgaris, and Lactococcus lactis. Thus, it is important to develop technologies, including high-throughput techniques, aimed at studying gene expression regulation at the level of translation. In the current study, we performed proteomic profiling of M. gallisepticum ribosomes and identified high abundant noncanonical proteins. We found that binding of mRNAs to ribosomes is mainly determined by two parameters: (1) abundance of mRNA itself and (2) complimentary interactions between the 3 end of 16S rRNA and the ribosome binding site in the 5-untranslated region of mRNA.

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Ong, Seeu Si, Jia Xu, Choon Kiat Sim, Alexis Jiaying Khng, Peh Joo Ho, Philip Kam Weng Kwan, Aarthi Ravikrishnan, et al. "Profiling Microbial Communities in Idiopathic Granulomatous Mastitis." International Journal of Molecular Sciences 24, no. 2 (January 5, 2023): 1042. http://dx.doi.org/10.3390/ijms24021042.

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Idiopathic granulomatous mastitis (IGM) is a rare and benign inflammatory breast disease with ambiguous aetiology. Contrastingly, lactational mastitis (LM) is commonly diagnosed in breastfeeding women. To investigate IGM aetiology, we profiled the microbial flora of pus and skin in patients with IGM and LM. A total of 26 patients with IGM and 6 patients with LM were included in the study. The 16S rRNA sequencing libraries were constructed from 16S rRNA gene amplified from total DNA extracted from pus and skin swabs in patients with IGM and LM controls. Constructed libraries were multiplexed and paired-end sequenced on HiSeq4000. Metagenomic analysis was conducted using modified microbiome abundance analysis suite customised R-resource for paired pus and skin samples. Microbiome multivariable association analyses were performed using linear models. A total of 21 IGM and 3 LM paired pus and skin samples underwent metagenomic analysis. Bray−Curtis ecological dissimilarity distance showed dissimilarity across four sample types (IGM pus, IGM skin, LM pus, and LM skin; PERMANOVA, p < 0.001). No characteristic dominant genus was observed across the IGM samples. The IGM pus samples were more diverse than corresponding IGM skin samples (Shannon and Simpson index; Wilcoxon paired signed-rank tests, p = 0.022 and p = 0.07). Corynebacterium kroppenstedtii, reportedly associated with IGM in the literature, was higher in IGM pus samples than paired skin samples (Wilcoxon, p = 0.022). Three other species and nineteen genera were statistically significant in paired IGM pus–skin comparison after antibiotic treatment adjustment and multiple comparisons correction. Microbial profiles are unique between patients with IGM and LM. Inter-patient variability and polymicrobial IGM pus samples cannot implicate specific genus or species as an infectious cause for IGM.

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Ditz, Benedikt, Stephanie Christenson, John Rossen, Chris Brightling, Huib A. M. Kerstjens, Maarten van den Berge, and Alen Faiz. "Sputum microbiome profiling in COPD: beyond singular pathogen detection." Thorax 75, no. 4 (January 29, 2020): 338–44. http://dx.doi.org/10.1136/thoraxjnl-2019-214168.

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Culture-independent microbial sequencing techniques have revealed that the respiratory tract harbours a complex microbiome not detectable by conventional culturing methods. The contribution of the microbiome to chronic obstructive pulmonary disease (COPD) pathobiology and the potential for microbiome-based clinical biomarkers in COPD are still in the early phases of investigation. Sputum is an easily obtainable sample and has provided a wealth of information on COPD pathobiology, and thus has been a preferred sample type for microbiome studies. Although the sputum microbiome likely reflects the respiratory microbiome only in part, there is increasing evidence that microbial community structure and diversity are associated with disease severity and clinical outcomes, both in stable COPD and during the exacerbations. Current evidence has been limited to mainly cross-sectional studies using 16S rRNA gene sequencing, attempting to answer the question ‘who is there?’ Longitudinal studies using standardised protocols are needed to answer outstanding questions including differences between sputum sampling techniques. Further, with advancing technologies, microbiome studies are shifting beyond the examination of the 16S rRNA gene, to include whole metagenome and metatranscriptome sequencing, as well as metabolome characterisation. Despite being technically more challenging, whole-genome profiling and metabolomics can address the questions ‘what can they do?’ and ‘what are they doing?’ This review provides an overview of the basic principles of high-throughput microbiome sequencing techniques, current literature on sputum microbiome profiling in COPD, and a discussion of the associated limitations and future perspectives.

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Hu, Anyi, Nianzhi Jiao, Rui Zhang, and Zao Yang. "Niche Partitioning of Marine Group I Crenarchaeota in the Euphotic and Upper Mesopelagic Zones of the East China Sea." Applied and Environmental Microbiology 77, no. 21 (August 26, 2011): 7469–78. http://dx.doi.org/10.1128/aem.00294-11.

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ABSTRACTMarine group ICrenarchaeota(MGI) represents a ubiquitous and numerically predominant microbial population in marine environments. An understanding of the spatial dynamics of MGI and its controlling mechanisms is essential for an understanding of the role of MGI in energy and element cycling in the ocean. In the present study, we investigated the diversity and abundance of MGI in the East China Sea (ECS) by analysis of crenarchaeal 16S rRNA gene, the ammonia monooxygenase geneamoA, and the biotin carboxylase geneaccA. Quantitative PCR analyses revealed that these genes were higher in abundance in the mesopelagic than in the euphotic zone. In addition, the crenarchaealamoAgene was positively correlated with the copy number of the MGI 16S rRNA gene, suggesting that most of the MGI in the ECS are nitrifiers. Furthermore, the ratios of crenarchaealaccAtoamoAor to MGI 16S rRNA genes increased from the euphotic to the mesopelagic zone, suggesting that the role of MGI in carbon cycling may change from the epipelagic to the mesopelagic zones. Denaturing gradient gel electrophoretic profiling of the 16S rRNA genes revealed depth partitioning in MGI community structures. Clone libraries of the crenarchaealamoAandaccAgenes showed both “shallow” and “deep” groups, and their relative abundances varied in the water column. Ecotype simulation analysis revealed that MGI in the upper ocean could diverge into special ecotypes associated with depth to adapt to the light gradient across the water column. Overall, our results showed niche partitioning of the MGI population and suggested a shift in their ecological functions between the euphotic and mesopelagic zones of the ECS.

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Ezeoke, Ifeoma, Hans-Peter Klenk, Gabriele Pötter, Peter Schumann, Ben D. Moser, Brent A. Lasker, Ainsley Nicholson, and June M. Brown. "Nocardia amikacinitolerans sp. nov., an amikacin-resistant human pathogen." International Journal of Systematic and Evolutionary Microbiology 63, Pt_3 (March 1, 2013): 1056–61. http://dx.doi.org/10.1099/ijs.0.039990-0.

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Five nocardioform isolates from human clinical sources were evaluated. Analysis of the nearly full-length 16S rRNA gene showed 99.9–100 % similarity among the strains. The results of a comparative phylogenetic analysis of the 16S rRNA gene sequences indicated that the isolates belonged to the genus Nocardia . Phenotypic and molecular analyses were performed on the clinical isolates. Traditional phenotypic analyses included morphological, biochemical/physiological, chemotaxonomic and antimicrobial susceptibility profiling. Molecular studies included 1441-bp 16S rRNA and 1246-bp gyrB gene sequence analyses, as well as DNA–DNA hybridizations. Biochemical analysis failed to differentiate the putative novel species from its phylogenetic neighbours; however, molecular studies were able to distinguish the patient strains and confirm them as members of a single species. Based on 16S rRNA gene sequence analysis, similarity between the isolates and their closest relatives (type strains of Nocardia araoensis , N. arthritidis , N. beijingensis and N. niwae ) was ≤99.3 %. Analysis of partial gyrB gene sequences showed 98–99.7 % relatedness among the isolates. Nocardia lijiangensis and N. xishanensis were the closest related species to the isolates based on gyrB gene sequence analysis, and their type strains showed 95.7 and 95.3 % similarity, respectively, to strain W9988T. Resistance to amikacin and molecular analyses, including DNA–DNA hybridization, distinguished the five patient strains from their phylogenetic neighbours, and the results of this polyphasic study indicated the existence of a novel species of Nocardia , for which we propose the name Nocardia amikacinitolerans sp. nov., with strain W9988T ( = DSM 45539T = CCUG 59655T) as the type strain.

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39

Markusková, Barbora, Jana Minarovičová, Adriana Véghová, Hana Drahovská, and Eva Kaclíková. "Impact of DNA extraction methods on 16S rRNA-based profiling of bacterial communities in cheese." Journal of Microbiological Methods 184 (May 2021): 106210. http://dx.doi.org/10.1016/j.mimet.2021.106210.

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40

Han, Dongsheng, Peng Gao, Rui Li, Ping Tan, Jiehong Xie, Rui Zhang, and Jinming Li. "Multicenter assessment of microbial community profiling using 16S rRNA gene sequencing and shotgun metagenomic sequencing." Journal of Advanced Research 26 (November 2020): 111–21. http://dx.doi.org/10.1016/j.jare.2020.07.010.

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41

Frolov, Evgenii N., Alexandra V. Gololobova, Alexandra A. Klyukina, Elizaveta A. Bonch-Osmolovskaya, Nikolay V. Pimenov, Nikolay A. Chernyh, and Alexander Y. Merkel. "Diversity and Activity of Sulfate-Reducing Prokaryotes in Kamchatka Hot Springs." Microorganisms 9, no. 10 (October 1, 2021): 2072. http://dx.doi.org/10.3390/microorganisms9102072.

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Microbial communities of the Kamchatka Peninsula terrestrial hot springs were studied using radioisotopic and cultural approaches, as well as by the amplification and sequencing of dsrB and 16S rRNA genes fragments. Radioisotopic experiments with 35S-labeled sulfate showed that microbial communities of the Kamchatka hot springs are actively reducing sulfate. Both the cultivation experiments and the results of dsrB and 16S rRNA genes fragments analyses indicated the presence of microorganisms participating in the reductive part of the sulfur cycle. It was found that sulfate-reducing prokaryotes (SRP) belonging to Desulfobacterota, Nitrospirota and Firmicutes phyla inhabited neutral and slightly acidic hot springs, while bacteria of phylum Thermodesulofobiota preferred moderately acidic hot springs. In high-temperature acidic springs sulfate reduction was mediated by archaea of the phylum Crenarchaeota, chemoorganoheterotrophic representatives of genus Vulcanisaeta being the most probable candidates. The 16S rRNA taxonomic profiling showed that in most of the studied communities SRP was present only as a minor component. Only in one microbial community, the representatives of genus Vulcanisaeta comprised a significant group. Thus, in spite of comparatively low sulfate concentrations in terrestrial hot springs of the Kamchatka, phylogenetically and metabolically diverse groups of sulfate-reducing prokaryotes are operating there coupling carbon and sulfur cycles in these habitats.

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42

Mutignani, Massimiliano, Roberto Penagini, Giorgio Gargari, Simone Guglielmetti, Marcello Cintolo, Aldo Airoldi, Pierfrancesco Leone, et al. "Blood Bacterial DNA Load and Profiling Differ in Colorectal Cancer Patients Compared to Tumor-Free Controls." Cancers 13, no. 24 (December 18, 2021): 6363. http://dx.doi.org/10.3390/cancers13246363.

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Inflammation and immunity are linked to intestinal adenoma (IA) and colorectal cancer (CRC) development. The gut microbiota is associated with CRC risk. Epithelial barrier dysfunction can occur, possibly leading to increased intestinal permeability in CRC patients. We conducted a case-control study including 100 incident histologically confirmed CRC cases, and 100 IA and 100 healthy subjects, matched to cases by center, sex and age. We performed 16S rRNA gene analysis of blood and applied conditional logistic regression. Further analyses were based on negative binomial distribution normalization and Random Forest algorithm. We found an overrepresentation of blood 16S rRNA gene copies in colon cancer as compared to tumor-free controls. For high levels of gene copies, community diversity was higher in colon cancer cases than controls. Bacterial taxa and operational taxonomic unit abundances were different between groups and were able to predict CRC with an accuracy of 0.70. Our data support the hypothesis of a higher passage of bacteria from gastrointestinal tract to bloodstream in colon cancer. This result can be applied on non-invasive diagnostic tests for colon cancer control.

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43

Santiago-Rodriguez, Tasha M., Aaron Garoutte, Emmase Adams, Waleed Nasser, Matthew C. Ross, Alex La Reau, Zachariah Henseler, et al. "Metagenomic Information Recovery from Human Stool Samples Is Influenced by Sequencing Depth and Profiling Method." Genes 11, no. 11 (November 21, 2020): 1380. http://dx.doi.org/10.3390/genes11111380.

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Sequencing of the 16S rRNA gene (16S) has long been a go-to method for microbiome characterization due to its accessibility and lower cost compared to shotgun metagenomic sequencing (SMS). However, 16S sequencing rarely provides species-level resolution and cannot provide direct assessment of other taxa (e.g., viruses and fungi) or functional gene content. Shallow shotgun metagenomic sequencing (SSMS) has emerged as an approach to bridge the gap between 16S sequencing and deep metagenomic sequencing. SSMS is cost-competitive with 16S sequencing, while also providing species-level resolution and functional gene content insights. In the present study, we evaluated the effects of sequencing depth on marker gene-mapping- and alignment-based annotation of bacteria in healthy human stool samples. The number of identified taxa decreased with lower sequencing depths, particularly with the marker gene-mapping-based approach. Other annotations, including viruses and pathways, also showed a depth-dependent effect on feature recovery. These results refine the understanding of the suitability and shortcomings of SSMS, as well as annotation tools for metagenomic analyses in human stool samples. Results may also translate to other sample types and may open the opportunity to explore the effect of sequencing depth and annotation method.

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Murovec, Boštjan, Leon Deutsch, and Blaž Stres. "General Unified Microbiome Profiling Pipeline (GUMPP) for Large Scale, Streamlined and Reproducible Analysis of Bacterial 16S rRNA Data to Predicted Microbial Metagenomes, Enzymatic Reactions and Metabolic Pathways." Metabolites 11, no. 6 (May 24, 2021): 336. http://dx.doi.org/10.3390/metabo11060336.

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General Unified Microbiome Profiling Pipeline (GUMPP) was developed for large scale, streamlined and reproducible analysis of bacterial 16S rRNA data and prediction of microbial metagenomes, enzymatic reactions and metabolic pathways from amplicon data. GUMPP workflow introduces reproducible data analyses at each of the three levels of resolution (genus; operational taxonomic units (OTUs); amplicon sequence variants (ASVs)). The ability to support reproducible analyses enables production of datasets that ultimately identify the biochemical pathways characteristic of disease pathology. These datasets coupled to biostatistics and mathematical approaches of machine learning can play a significant role in extraction of truly significant and meaningful information from a wide set of 16S rRNA datasets. The adoption of GUMPP in the gut-microbiota related research enables focusing on the generation of novel biomarkers that can lead to the development of mechanistic hypotheses applicable to the development of novel therapies in personalized medicine.

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Pesapane, Risa, Andrea Chaves, Janet Foley, Nadia Javeed, Samantha Barnum, Katherine Greenwald, Erin Dodd, et al. "Nasopulmonary mites (Acari: Halarachnidae) as potential vectors of bacterial pathogens, including Streptococcus phocae, in marine mammals." PLOS ONE 17, no. 6 (June 16, 2022): e0270009. http://dx.doi.org/10.1371/journal.pone.0270009.

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Nasopulmonary mites (NPMs) of the family Halarachnidae are obligate endoparasites that colonize the respiratory tracts of mammals. NPMs damage surface epithelium resulting in mucosal irritation, respiratory illness, and secondary infection, yet the role of NPMs in facilitating pathogen invasion or dissemination between hosts remains unclear. Using 16S rRNA massively parallel amplicon sequencing of six hypervariable regions (or “16S profiling”), we characterized the bacterial community of NPMs from 4 southern sea otters (Enhydra lutris nereis). This data was paired with detection of a priority pathogen, Streptococcus phocae, from NPMs infesting 16 southern sea otters and 9 California sea lions (Zalophus californianus) using nested conventional polymerase chain reaction (nPCR). The bacteriome of assessed NPMs was dominated by Mycoplasmataceae and Vibrionaceae, but at least 16 organisms with pathogenic potential were detected as well. Importantly, S. phocae was detected in 37% of NPM by nPCR and was also detected by 16S profiling. Detection of multiple organisms with pathogenic potential in or on NPMs suggests they may act as mechanical vectors of bacterial infection for marine mammals.

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46

Nishizawa, Tomoyasu, Yasuko Neagari, Takamasa Miura, Munehiko Asayama, Koichi Murata, Ken-Ichi Harada, and Makoto Shirai. "Molecular Analysis of the Cyanobacterial Community in Gastric Contents of Egrets with Symptoms of Steatitis." Open Microbiology Journal 9, no. 1 (November 3, 2015): 160–66. http://dx.doi.org/10.2174/1874285801509010160.

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Many deaths of wild birds that have drunk water contaminated with hepatotoxic microcystin-producing cyanobacteria have been reported. A mass death of egrets and herons with steatitis were found at the agricultural reservoir occurring cyanobacterial waterblooms. This study aimed to verify a hypothesis that the egrets and herons which died in the reservoir drink microcystin-producing cyanobacteria and microcystin involves in the cause of death as well as the symptoms of steatitis. The cyanobacterial community in gastric contents of egrets and herons that died from steatitis was assessed using cyanobacterial 16S rRNA-based terminal-restriction fragment length polymorphism (T-RFLP) profiling and a cyanobacterial 16S rRNA-based clone library analysis. In addition, PCR amplification of the mcyB–C region and the mcyG gene, involved in microcystin biosynthesis, was examined. The cyanobacterial community in the gastric contents of two birds showed a simplistic composition. A comparison of cyanobacterial T-RFLP profiling and cloned sequences suggested that the genus Microcystis predominated in both samples of egrets died. Although we confirmed that two egrets which died in the reservoir have taken in cyanobacterial waterblooms containing the genus Microcystis, no mcy gene was detected in both samples according to the mcy gene-based PCR analysis. This study is the first to show the profiling and traceability of a cyanobacterial community in the gastric contents of wild birds by molecular analysis. Additionally, we consider causing symptoms of steatitis in the dead egrets.

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47

Thomas, Pious, and Christopher M. M. Franco. "Intracellular Bacteria in Plants: Elucidation of Abundant and Diverse Cytoplasmic Bacteria in Healthy Plant Cells Using In Vitro Cell and Callus Cultures." Microorganisms 9, no. 2 (January 28, 2021): 269. http://dx.doi.org/10.3390/microorganisms9020269.

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This study was initiated to assess whether the supposedly axenic plant cell cultures harbored any cultivation-recalcitrant endophytic bacteria (CREB). Adopting live-cell imaging with bright-field, fluorescent and confocal microscopy and bacterial 16S-rRNA gene taxonomic profiling, we report the cytoplasmic association of abundant and diverse CREBs in long-term actively maintained callus and cell suspension cultures of different plant species. Preliminary bright-field live-cell imaging on grape cell cultures showed abundant intracellular motile micro-particles resembling bacteria, which proved uncultivable on enriched media. Bacterial probing employing DNA stains, transmission electron microscopy, and Eubacterial FISH indicated abundant and diverse cytoplasmic bacteria. Observations on long-term maintained/freshly established callus stocks of different plant species—grapevine, barley, tobacco, Arabidopsis, and medicinal species—indicated intracellular bacteria as a common phenomenon apparently originating from field shoot tissues.Cultivation-independent 16S rRNA gene V3/V3–V4 amplicon profiling on 40-year-old grape cell/callus tissues revealed a high bacterial diversity (>250 genera), predominantly Proteobacteria, succeeded by Firmicutes, Actinobacteria, Bacteriodetes, Planctomycetes, and 20 other phyla, including several candidate phyla. PICRUSt analysis revealed diverse functional roles for the bacterial microbiome, majorly metabolic pathways. Thus, we unearth the widespread association of cultivation-recalcitrant intracellular bacteria “Cytobacts” inhabiting healthy plant cells, sharing a dynamic mutualistic association with cell hosts.

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Yen, Sandi, Jethro Johnson, and Nicholas E. Ilott. "Streamlined processing and analysis of 16S rRNA amplicon sequencing data with OCMS_16S and OCMSlooksy." Wellcome Open Research 7 (February 23, 2022): 68. http://dx.doi.org/10.12688/wellcomeopenres.17632.1.

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16S rRNA gene sequencing is a cost-effective method for profiling the bacterial component of a microbiome. Nevertheless, processing and analysis of the resulting sequencing data is often constrained by the availability of dedicated bioinformaticians - creating a bottleneck for biological interpretation. Multiple visualisation and analysis tools now exist for downstream analysis of 16S rRNA data. These tools are designed with biological scientists in mind and therefore consist of a graphical user interface that interacts with taxonomic counts tables to perform tasks such as alpha- and beta-diversity analysis and differential abundance. However, generating the input to these applications still relies on bioinformatics experience, creating a disconnect between data processing and data analysis. We aimed to bridge the gap between data processing and data analysis. To do this we have created two tools - OCMS_16S and OCMSlooksy - that perform data processing and data visualisation/analysis, respectively. OCMS_16S is a cgat-core based pipeline that wraps DADA2 functionality in order to facilitate processing of raw sequence reads into tables of amplicon sequence variant (ASV) counts using a simple command line interface. OCMSlooksy is an RShiny application that takes an OCMS_16S-generated SQLite database as input to facilitate data exploration and analysis. Combining these tools provides a simple, user-friendly workflow to facilitate 16S rRNA gene amplicon sequencing data analysis from raw reads to results.

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Ding, N. S., J. A. K. McDonald, A. Perdones-Montero, Douglas N. Rees, S. O. Adegbola, R. Misra, P. Hendy, et al. "Metabonomics and the Gut Microbiome Associated With Primary Response to Anti-TNF Therapy in Crohn’s Disease." Journal of Crohn's and Colitis 14, no. 8 (March 2, 2020): 1090–102. http://dx.doi.org/10.1093/ecco-jcc/jjaa039.

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Abstract Background and Aims Anti-tumour necrosis factor [anti-TNF] therapy is indicated for treatment of moderate to severe inflammatory bowel disease [IBD], but has a primary non-response rate of around 30%. We aim to use metabonomic and metataxonomic profiling to identify predictive biomarkers of anti-TNF response in Crohn’s disease. Methods Patients with luminal Crohn’s disease, commencing anti-TNF therapy, were recruited with urine, faeces, and serum samples being collected at baseline and 3-monthly. Primary response was defined according to a combination of clinical and objective markers of inflammation. Samples were measured using three UPLC-MS assays: lipid, bile acid, and Hydrophillic Interaction Liquid Chromatography [HILIC] profiling with 16S rRNA gene sequencing of faeces. Results Samples were collected from 76 Crohn’s disease patients who were anti-TNF naïve and from 13 healthy controls. There were 11 responders, 37 non-responders, and 28 partial responders in anti-TNF-treated Crohn’s patients. Histidine and cysteine were identified as biomarkers of response from polar metabolite profiling [HILIC] of serum and urine. Lipid profiling of serum and faeces found phosphocholines, ceramides, sphingomyelins, and triglycerides, and bile acid profiling identified primary bile acids to be associated with non-response to anti-TNF therapy, with higher levels of phase 2 conjugates in non-responders. Receiver operating curves for treatment response demonstrated 0.94 +/ -0.10 [faecal lipid], 0.81 +/- 0.17 [faecal bile acid], and 0.74 +/- 0.15 [serum bile acid] predictive ability for anti-TNF response in Crohn’s disease. Conclusions This prospective, longitudinal cohort study of metabonomic and 16S rRNA gene sequencing analysis demonstrates that a range of metabolic biomarkers involving lipid, bile acid, and amino acid pathways may contribute to prediction of response to anti-TNF therapy in Crohn’s disease. Podcast This article has an associated podcast which can be accessed at https://academic.oup.com/ecco-jcc/pages/podcast

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Lagkouvardos, Ilias, Sandra Fischer, Neeraj Kumar, and Thomas Clavel. "Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons." PeerJ 5 (January 11, 2017): e2836. http://dx.doi.org/10.7717/peerj.2836.

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The importance of 16S rRNA gene amplicon profiles for understanding the influence of microbes in a variety of environments coupled with the steep reduction in sequencing costs led to a surge of microbial sequencing projects. The expanding crowd of scientists and clinicians wanting to make use of sequencing datasets can choose among a range of multipurpose software platforms, the use of which can be intimidating for non-expert users. Among available pipeline options for high-throughput 16S rRNA gene analysis, the R programming language and software environment for statistical computing stands out for its power and increased flexibility, and the possibility to adhere to most recent best practices and to adjust to individual project needs. Here we present the Rhea pipeline, a set of R scripts that encode a series of well-documented choices for the downstream analysis of Operational Taxonomic Units (OTUs) tables, including normalization steps,alpha- andbeta-diversity analysis, taxonomic composition, statistical comparisons, and calculation of correlations. Rhea is primarily a straightforward starting point for beginners, but can also be a framework for advanced users who can modify and expand the tool. As the community standards evolve, Rhea will adapt to always represent the current state-of-the-art in microbial profiles analysis in the clear and comprehensive way allowed by the R language. Rhea scripts and documentation are freely available athttps://lagkouvardos.github.io/Rhea.

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