16rrna.org 16s, Metagenome, 18s, Microbial Sequencing

21. Food Microbiol. 2015 Apr;46:342-56. doi: 10.1016/j.fm.2014.08.023. Epub 2014 Sep



Bacterial diversity in typical Italian salami at different ripening stages as

revealed by high-throughput sequencing of 16S rRNA amplicons.


Połka J(1), Rebecchi A(2), Pisacane V(2), Morelli L(1), Puglisi E(3).


Author information:

(1)Istituto di Microbiologia, Facoltà di Scienze Agrarie, Alimentari ed

Ambientali, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122

Piacenza, Italy. (2)Centro Ricerche Biotecnologiche, Università Cattolica del

Sacro Cuore, Via Milano 24, 26100 Cremona, Italy. (3)Istituto di Microbiologia,

Facoltà di Scienze Agrarie, Alimentari ed Ambientali, Università Cattolica del

Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italy. Electronic address:



Erratum in

    Food Microbiol. 2015 Jun;48:191.


The bacterial diversity involved in food fermentations is one of the most

important factors shaping the final characteristics of traditional foods.

Knowledge about this diversity can be greatly improved by the application of

high-throughput sequencing technologies (HTS) coupled to the PCR amplification of

the 16S rRNA subunit. Here we investigated the bacterial diversity in batches of

Salame Piacentino PDO (Protected Designation of Origin), a dry fermented sausage

that is typical of a regional area of Northern Italy. Salami samples from 6

different local factories were analysed at 0, 21, 49 and 63 days of ripening; raw

meat at time 0 and casing samples at 21 days of ripening where also analysed, and

the effect of starter addition was included in the experimental set-up.

Culture-based microbiological analyses and PCR-DGGE were carried out in order to

be compared with HTS results. A total of 722,196 high quality sequences were

obtained after trimming, paired-reads assembly and quality screening of raw reads

obtained by Illumina MiSeq sequencing of the two bacterial 16S hypervariable

regions V3 and V4; manual curation of 16S database allowed a correct taxonomical

classification at the species for 99.5% of these reads. Results confirmed the

presence of main bacterial species involved in the fermentation of salami as

assessed by PCR-DGGE, but with a greater extent of resolution and quantitative

assessments that are not possible by the mere analyses of gel banding patterns.

Thirty-two different Staphylococcus and 33 Lactobacillus species where identified

in the salami from different producers, while the whole data set obtained

accounted for 13 main families and 98 rare ones, 23 of which were present in at

least 10% of the investigated samples, with casings being the major sources of

the observed diversity. Multivariate analyses also showed that batches from 6

local producers tend to cluster altogether after 21 days of ripening, thus

indicating that HTS has the potential for fine scale differentiation of local

fermented foods.


Copyright © 2014 Elsevier Ltd. All rights reserved.


DOI: 10.1016/j.fm.2014.08.023

PMID: 25475305  [PubMed - indexed for MEDLINE]



22. BMC Genomics. 2016 Jan 14;17:55. doi: 10.1186/s12864-015-2194-9.


A comprehensive benchmarking study of protocols and sequencing platforms for 16S

rRNA community profiling.


D'Amore R(1), Ijaz UZ(2), Schirmer M(3), Kenny JG(4), Gregory R(5), Darby AC(6),

Shakya M(7), Podar M(8), Quince C(9), Hall N(10).


Author information:

(1)Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB,

UK. linda.damore@liverpool.ac.uk. (2)School of Engineering, University of

Glasgow, Glasgow, G12 8LT, UK. Umer.Ijaz@glasgow.ac.uk. (3)School of Engineering,

University of Glasgow, Glasgow, G12 8LT, UK. melanie@broadinstitute.org.

(4)Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB,

UK. jkenny@liv.ac.uk. (5)Institute of Integrative Biology, University of

Liverpool, Liverpool, L69 7ZB, UK. greg@liv.ac.uk. (6)Institute of Integrative

Biology, University of Liverpool, Liverpool, L69 7ZB, UK. (7)Department of

Biological Sciences, Dartmouth College, Hanover, NH03755, USA.

microbeatic@gmail.com. (8)Biosciences Division, Oak Ridge National Laboratory,

Oak Ridge, 37831, TN, USA. podarm@ornl.gov. (9)Warwick Medical School, University

of Warwick, Warwick, CV4 7AL, UK. C.Quince@warwick.ac.uk. (10)Institute of

Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK.



BACKGROUND: In the last 5 years, the rapid pace of innovations and improvements

in sequencing technologies has completely changed the landscape of metagenomic

and metagenetic experiments. Therefore, it is critical to benchmark the various

methodologies for interrogating the composition of microbial communities, so that

we can assess their strengths and limitations. The most common phylogenetic

marker for microbial community diversity studies is the 16S ribosomal RNA gene

and in the last 10 years the field has moved from sequencing a small number of

amplicons and samples to more complex studies where thousands of samples and

multiple different gene regions are interrogated.

RESULTS: We assembled 2 synthetic communities with an even (EM) and uneven (UM)

distribution of archaeal and bacterial strains and species, as metagenomic

control material, to assess performance of different experimental strategies. The

2 synthetic communities were used in this study, to highlight the limitations and

the advantages of the leading sequencing platforms: MiSeq (Illumina), The Pacific

Biosciences RSII, 454 GS-FLX/+ (Roche), and IonTorrent (Life Technologies). We

describe an extensive survey based on synthetic communities using 3 experimental

designs (fusion primers, universal tailed tag, ligated adaptors) across the 9

hypervariable 16S rDNA regions. We demonstrate that library preparation

methodology can affect data interpretation due to different error and chimera

rates generated during the procedure. The observed community composition was

always biased, to a degree that depended on the platform, sequenced region and

primer choice. However, crucially, our analysis suggests that 16S rRNA sequencing

is still quantitative, in that relative changes in abundance of taxa between

samples can be recovered, despite these biases.

CONCLUSION: We have assessed a range of experimental conditions across several

next generation sequencing platforms using the most up-to-date configurations. We

propose that the choice of sequencing platform and experimental design needs to

be taken into consideration in the early stage of a project by running a small

trial consisting of several hypervariable regions to quantify the discriminatory

power of each region. We also suggest that the use of a synthetic community as a

positive control would be beneficial to identify the potential biases and

procedural drawbacks that may lead to data misinterpretation. The results of this

study will serve as a guideline for making decisions on which experimental

condition and sequencing platform to consider to achieve the best microbial



DOI: 10.1186/s12864-015-2194-9

PMCID: PMC4712552

PMID: 26763898  [PubMed - indexed for MEDLINE]



23. BMC Microbiol. 2016 Jul 11;16(1):145. doi: 10.1186/s12866-016-0758-8.


High-throughput sequencing of 16S rRNA Gene Reveals Substantial Bacterial

Diversity on the Municipal Dumpsite.


Mwaikono KS(1,)(2), Maina S(3), Sebastian A(4), Schilling M(5), Kapur V(6,)(5),

Gwakisa P(6,)(7).


Author information:

(1)Department of Science and Laboratory Technology, Dar es Salaam Institute of

Technology, Dar es Salaam, Tanzania. kilazasmsn24@gmail.com. (2)School of Life

Sciences and Bioengineering, The Nelson Mandela African Institution of Science

and Technology, P.O. Box 447, Arusha, Tanzania. kilazasmsn24@gmail.com.

(3)BecA-ILRI Hub International Livestock Research Institute, P. O. Box 30709,

Nairobi, Kenya. (4)Departments of Biochemistry and Molecular Biology, W238A

Millennium Science Complex, Penn State University, University Park, PA, 16802,

USA. (5)Huck Institutes of Life Sciences, Molecular Cellular and Integrative

Biosciences, the Pennsylvania State University, 204 Wartik Laboratories,

University Park, PA, 16802, USA. (6)School of Life Sciences and Bioengineering,

The Nelson Mandela African Institution of Science and Technology, P.O. Box 447,

Arusha, Tanzania. (7)Genome Sciences Centre, Faculty of Veterinary Medicine,

Sokoine University of Agriculture, Morogoro, Tanzania.


BACKGROUND: Multiple types of solid waste in developing countries is disposed of

together in dumpsites where there is interaction between humans, animals and the

bacteria in the waste. To study the bacteria at the dumpsite and the associated

risks, previous studies have focused on culturable, leaving behind a great number

of unculturable bacteria. This study focuses on a more comprehensive approach to

study bacteria at the dumpsite. Since the site comprised of unsorted wastes, a

qualitative survey was first performed to identify the variety of solid waste as

this has influence on the microbial composition. Thus, domestic (Dom), biomedical

(Biom), river sludge (Riv), and fecal material of pigs scavenging on the dumpsite

(FecD) were sampled. Total DNA was extracted from 78 samples and the v4-16S rRNA

amplicons was characterized using an Illumina MiSeq platform.

RESULTS: A total of 8,469,294 sequences passed quality control. Catchall analysis

predicted a mean of 8243 species per sample. Diversity was high with an average

InvSimpson index of 44.21 ± 1.44. A total of 35 phyla were detected and the

predominant were Firmicutes (38 %), Proteobacteria (35 %), Bacteroidetes (13 %)

and Actinobacteria (3 %). Overall 76,862 OTUs were detected, however, only 20 %

were found more than 10 times. The predominant OTUs were Acinetobacter (12.1 %),

Clostridium sensu stricto (4.8 %), Proteinclasticum and Lactobacillus both at

(3.4 %), Enterococcus (2.9 %) and Escherichia/Shigella (1.7 %). Indicator

analysis (P ≤ 0.05, indicator value ≥ 70) shows that Halomonas, Idiomarina,

Tisierella and Proteiniclasticum were associated with Biom; Enterococcus,

Bifidobacteria, and Clostridium sensu stricto with FecD and Flavobacteria,

Lysobacter and Commamonas to Riv. Acinetobacter and Clostridium sensu stricto

were found in 62 % and 49 % of all samples, respectively, at the relative

abundance of 1 %. None of OTUs was found across all samples.

CONCLUSIONS: This study provides a comprehensive report on the abundance and

diversity bacteria in municipal dumpsite. The species richness reported here

shows the complexity of this man-made ecosystem and calls for further research to

assess for a link between human diseases and the dumpsite. This would provide

insight into proper disposal of the waste, as well as, limit the risks to human

health associated with the dumpsite.


DOI: 10.1186/s12866-016-0758-8

PMCID: PMC4940873

PMID: 27400733  [PubMed - in process]



24. Insect Sci. 2015 Oct;22(5):606-18. doi: 10.1111/1744-7917.12155. Epub 2014 Nov



Bacterial community structure in Apis florea larvae analyzed by denaturing

gradient gel electrophoresis and 16S rRNA gene sequencing.


Saraithong P(1,)(2), Li Y(2), Saenphet K(1), Chen Z(2), Chantawannakul P(1,)(3).


Author information:

(1)Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai,

50200, Thailand. (2)Department of Basic Science and Craniofacial Biology, New

York University College of Dentistry, New York, 10010, USA. (3)Materials Science

Research Center, Faculty of Science, Chiang Mai University, Chiang Mai, 50200,



This study characterizes the colonization and composition of bacterial flora in

dwarf Asian honeybee (Apis florea) larvae and compares bacterial diversity and

distribution among different sampling locations. A. florea larvae were collected

from 3 locations in Chiang Mai province, Thailand. Bacterial DNA was extracted

from each larva using the phenol-chloroform method. Denaturing gradient gel

electrophoresis was performed, and the dominant bands were excised from the gels,

cloned, and sequenced for bacterial species identification. The result revealed

similarities of bacterial community profiles in each individual colony, but

differences between colonies from the same and different locations. A. florea

larvae harbor bacteria belonging to 2 phyla (Firmicutes and Proteobacteria), 5

classes (Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Bacilli,

and Clostridia), 6 genera (Clostridium, Gilliamella, Melissococcus,

Lactobacillus, Saccharibacter, and Snodgrassella), and an unknown genus from

uncultured bacterial species. The classes with the highest abundance of bacteria

were Alphaproteobacteria (34%), Bacilli (25%), Betaproteobacteria (11%),

Gammaproteobacteria (10%), and Clostridia (8%), respectively. Similarly,

uncultured bacterial species were identified (12%). Environmental bacterial

species, such as Saccharibacter floricola, were also found. This is the first

study in which sequences closely related to Melissococcus plutonius, the causal

pathogen responsible for European foulbrood, have been identified in Thai A.

florea larvae.


© 2014 Institute of Zoology, Chinese Academy of Sciences.


DOI: 10.1111/1744-7917.12155

PMID: 25393530  [PubMed - indexed for MEDLINE]



25. Front Microbiol. 2016 Aug 23;7:1297. doi: 10.3389/fmicb.2016.01297. eCollection



Evaluation of 16S rRNA Gene Primer Pairs for Monitoring Microbial Community

Structures Showed High Reproducibility within and Low Comparability between

Datasets Generated with Multiple Archaeal and Bacterial Primer Pairs.


Fischer MA(1), Güllert S(2), Neulinger SC(3), Streit WR(2), Schmitz RA(1).


Author information:

(1)Department of Biology, Institute for General Microbiology,

Christian-Albrechts-Universität zu Kiel Kiel, Germany. (2)Biozentrum Klein

Flottbek, Institute of Microbiology & Biotechnology, Universität Hamburg Hamburg,

Germany. (3)Department of Biology, Institute for General Microbiology,

Christian-Albrechts-Universität zu KielKiel, Germany; omics2view.consulting

GbRKiel, Germany.


The application of next-generation sequencing technology in microbial community

analysis increased our knowledge and understanding of the complexity and

diversity of a variety of ecosystems. In contrast to Bacteria, the archaeal

domain was often not particularly addressed in the analysis of microbial

communities. Consequently, established primers specifically amplifying the

archaeal 16S ribosomal gene region are scarce compared to the variety of primers

targeting bacterial sequences. In this study, we aimed to validate archaeal

primers suitable for high throughput next generation sequencing. Three archaeal

16S primer pairs as well as two bacterial and one general microbial 16S primer

pairs were comprehensively tested by in-silico evaluation and performing an

experimental analysis of a complex microbial community of a biogas reactor. The

results obtained clearly demonstrate that comparability of community profiles

established using different primer pairs is difficult. 16S rRNA gene data derived

from a shotgun metagenome of the same reactor sample added an additional

perspective on the community structure. Furthermore, in-silico evaluation of

primers, especially those for amplification of archaeal 16S rRNA gene regions,

does not necessarily reflect the results obtained in experimental approaches. In

the latter, archaeal primer pair ArchV34 showed the highest similarity to the

archaeal community structure compared to observed by the metagenomic approach and

thus appears to be the appropriate for analyzing archaeal communities in biogas

reactors. However, a disadvantage of this primer pair was its low specificity for

the archaeal domain in the experimental application leading to high amounts of

bacterial sequences within the dataset. Overall our results indicate a rather

limited comparability between community structures investigated and determined

using different primer pairs as well as between metagenome and 16S rRNA gene

amplicon based community structure analysis. This finding, previously shown for

Bacteria, was as well observed for the archaeal domain.


DOI: 10.3389/fmicb.2016.01297

PMCID: PMC4994424

PMID: 27602022  [PubMed]

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