De-MetaST-BLAST: A Tool for the Validation of
Degenerate Primer Sets and Data Mining of Publicly
Christopher A. Gulvik1, T. Chad Effler1,2, Steven W. Wilhelm1, Alison Buchan1*
1Department of Microbiology, University of Tennessee, Knoxville, Tennessee, United States of America, 2Department of Electrical Engineering and Computer Science,
University of Tennessee, Knoxville, Tennessee, United States of America
Development and use of primer sets to amplify nucleic acid sequences of interest is fundamental to studies spanning many
life science disciplines. As such, the validation of primer sets is essential. Several computer programs have been created to
aid in the initial selection of primer sequences that may or may not require multiple nucleotide combinations (i.e.,
degeneracies). Conversely, validation of primer specificity has remained largely unchanged for several decades, and there
are currently few available programs that allows for an evaluation of primers containing degenerate nucleotide bases. To
alleviate this gap, we developed the program De-MetaST that performs an in silico amplification using user defined
nucleotide sequence dataset(s) and primer sequences that may contain degenerate bases. The program returns an output
file that contains the in silico amplicons. When De-MetaST is paired with NCBI’s BLAST (De-MetaST-BLAST), the program also
returns the top 10 nr NCBI database hits for each recovered in silico amplicon. While the original motivation for
development of this search tool was degenerate primer validation using the wealth of nucleotide sequences available in
environmental metagenome and metatranscriptome databases, this search tool has potential utility in many data mining
Citation: Gulvik CA, Effler TC, Wilhelm SW, Buchan A (2012) De-MetaST-BLAST: A Tool for the Validation of Degenerate Primer Sets and Data Mining of Publicly
Available Metagenomes. PLoS ONE 7(11): e50362. doi:10.1371/journal.pone.0050362
Editor: David L. Kirchman, University of Delaware, United States of America
Received June 13, 2012; Accepted October 24, 2012; Published November 26, 2012
Copyright: ? 2012 Gulvik et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: TCE was supported by an REU award from the National Science Foundation (NSF) (MCB1112001 to SWW). SWW and AB acknowledge NSF award
OCE1061352 for support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
PCR is one of the most fundamental and powerful molecular
biology tools available. PCR primer sets that contain degenerate
bases allow for the amplification of homologous sequences and
have been used in various applications, including genetic diversity
analyses (e.g., [1–12]). Several software packages that use
a nucleotide or amino acid alignment of the genetic target are
available to aid in the initial development of degenerate primer
sets (e.g., Amplicon , CODEHOP [14–16], DEFOG ,
DePiCt , HYDEN , MAD-DPD , PhiSiGns , and
Primaclade ). In addition, manual identification of conserved
regions from aligned sequences generated using software such as
ARB , ClustalX , and MEGA  is also common
practice (e.g., [26–31]). Once candidate primers are developed,
thermodynamic properties and self-complementarity tests can be
obtained using online tools (e.g., OligoCalc ).
Despite the utility and common use of degenerate primers, there
are no software programs specifically designed to facilitate
validation of their specificity. The most common practice for
initial validation of degenerate primers is by direct sequence
analysis of PCR amplicons (e.g., [33–37]). This can be both
laborious and costly, and does not take advantage of the ever-
increasing publicly available nucleotide data, including that
derived from natural samples. In fact, environmental metagen-
omes and metatranscriptomes are especially attractive reference
databases (e.g., CAMERA  [http://camera.calit2.net/] and
MG-RAST [http://metagenomics.anl.gov/]) to perform in silico
tests en masse to identify sequences a degenerate primer set might
To address this gap in available bioinformatic tools, we have
developed a program termed De-MetaST. This program accepts
primers that are degenerate using a meta-genome and –
transcriptome search tool to retrieve in silico PCR amplicons.
When paired with BLAST , the output provides the most
homologous sequences in GenBank for each recovered in silico
amplicon. In this report, we provide an overview of the program
and outline its utility as a tool to validate the specificity of
degenerate primer sets. This program is designed to be user-
friendly for non-bioinformatics specialists and is publicly available;
as are screencast video tutorials demonstrating installation and
Design and Program Overview
De-MetaST is written in C++ and is provided as an
executable wrapper to include BLAST (De-MetaST-BLAST)
as well as an independent executable (De-MetaST). The
function of De-MetaST is to implement a search routine based
on bitwise comparisons. Initial steps translate the degenerate
nucleotide sequences of each primer, as well as their reverse
complementsequences,into uniqueand specificbinary
PLOS ONE | www.plosone.org1 November 2012 | Volume 7 | Issue 11 | e50362
representations. This approach facilitates rapid searches of large
databases that are also transformed into binary representations.
The specific computational steps of De-MetaST are outlined in
How De-MetaST Works
The De-MetaST program initially converts the inputted
primer sequences into 4-digit binary code, where the 16 possible
combinations of nucleotides include: A, T, C, G, B, D, H, K,
M, N (or X), R, S, V, W, and Y (Figure 1). Then, each
sequence read within a user defined, FASTA formatted
database is converted to 4-digit binary codes and scanned
using a bitwise searching operation for the presence of both
primer sequences inthe appropriate orientation. Limited
memory is necessary for this action because each sequence
read is individually transformed to binary and immediately
scanned for the presence of the primer sequences. The program
searches using both the original user inputted primers as well as
the reverse and complement of those sequences. This latter
search is done to insure identification of target sequences
regardless ofwhetherthe sense
represented by the database sequence read scanned. The search
feature also allows a single primer to serve as both the forward
and reverse primer. When primers identify their respective
target(s) within a sequence read, the nucleotide sequence
delimited by the two primers, termed the in silico amplicon, is
retrieved. The primer(s) yielding each amplicon are reported in
the output. De-MetaST is written to parse in silico amplicons
.5000 bp into a separate FASTA formatted file that is not
subject to BLASTx; users can modify this length restriction by
editing the code. All in silico amplicons provided in the output
represent the sense strand in a 59 to 39 orientation. Thus, when
positive hits are made to reads representing antisense strands,
the complement and reverse of those reads are generated. Any
identifying features (e.g., unique read number) as well as the file
name for each predicted hit is recovered. Although developed to
accept degenerate primers, non-degenerate primers can also be
input into De-MetaST. Furthermore, the nucleotide query
database(s) themselves may contain sequence reads with de-
generate or ambiguous nucleotides (e.g., N). Finally, De-MetaST
accepts multiple primer sets as input; the in silico amplicons from
each set are output into separate FASTA files. As De-MetaST
accepts degeneracies in the input primer sequences, it requires
absolute conservation in the target sequences; it does not allow
for any mismatches between the primer sequence and target. In
this way, the user controls the level of primer specificity.
De-MetaST Paired with BLAST
Once the database sequence files have been queried for
predicted PCR amplicons, each in silico amplicon is subject to
Figure 1. De-MetaST transformation of nucleotide sequences into a binary representation. The binary representation for each of the 16
possible nucleotide character inputs is shown in the upper box. The lower box provides an example of the transformation using a mock primer
sequence. Spaced gaps are shown for instructional purposes and do not occur in the De-MetaST search routine.
De-MetaST-BLAST: A Primer Validation Tool
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a BLASTx analysis, which translates the nucleotide sequence in all
six frames and performs queries for each translation against the
non-redundant (nr) NCBI protein database. The top 10 BLASTx
hits for each amplicon are formatted as an XML file. The final
step of De-MetaST-BLAST compiles all of the meta-information
of the BLASTx results for each amplicon retrieved (e.g., hit
accession number, E-value, predicted function, nucleotide se-
quence, database file name, the primer combination that retrieved
the amplicon, unique read number) into a single, tab-delimited
TXT file. The BLASTx results file can also be exported as an XLS
file format for direct use in Microsoft Excel or other suitable
program. A graphical overview of the De-MetaST-BLAST
workflow is shown in Figure 2.
Results and Discussion
We have developed a computational method to generate in silico
amplifications from degenerate primer sets searched against user
defined nucleotide databases. To illustrate the utility of De-
MetaST-BLAST, we demonstrate its performance using a novel
degenerate primer set designed for use on environmental samples.
This primer set targets the bacterial boxB gene, which encodes the
oxygenase component of a multi-enzyme epoxidase (EC 1.14.13)
that is specific to a benzoate catabolic pathway . Three
metagenome libraries representing different environments, library
size and DNA sequencing methods were searched and found to
contain putative boxB amplicons of the appropriate size (300 bp)
(Table 1). Figure 3 shows the typical output of De-MetaST-
BLAST for one of those database searches, which includes for
each in silico amplicon the top 10 BLASTx hits with their
corresponding E-value and GenBank accession number.
To retrieve an in silico amplicon, the program requires both
primers to match their respective targets in a single sequence read
or sequence assembly (contig). Thus, an important consideration
in terms of selection of appropriate searchable databases is the
average length of the sequence read or assembly contained within
it, as well as the desired amplicon size. This concern may be
alleviated as longer read sequencing technologies are developed
and/or as sequence coverage and assembly algorithms improve.
Interestingly, our analysis demonstrates that in silico amplicons of
Figure 2. Flowchart outlining De-MetaST-BLAST user actions and corresponding computational processes. Fwd, Forward; Rev, Reverse;
NCBI, National Center for Biotechnology Information.
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,300 bp and ,190 bp, representing boxB and 16S rRNA gene
amplicons, respectively, can be readily recovered from databases
dominated by short read length sequences (e.g. AntarcticaAquatic;
Table 1). In fact, the 44 boxB amplicons derived from the
AntarcticaAquatic dataset were found in reads that ranged from
348–541 bp in length. This result suggests that sequence coverage,
or depth, is also a contributing factor to in silico amplicon recovery.
Incidentally, all of the in silico amplicons recovered in this
demonstration run were found to be homologous to the desired
target (E-value #1e24).
In terms of data mining, De-MetaST can provide complemen-
tary sequence data for gene diversity studies. As the De-MetaST
output provides the sequence from the same genetic positions as
that derived from a companion clone library, downstream
analysis, such as sequence alignment and subsequent phylogenetic
analysis, is streamlined. Thus, in silico amplicons retrieved from
existing sequence datasets can be readily compared to experimen-
tally derived clone library sequences. Furthermore, as the
nucleotide sequences targeted by the primers are returned in the
De-MetaST output, users can draw on that information to further
refine their primers according to a desired level of functional and/
or phylogenetic specificity. The program also has utility beyond
searches of environmental sequence databases. It can be used to
query any nucleotide dataset, including those derived from single
organisms. Thus, it has use in assessing the specificity of primers
targeting multi-copy or homologous genes within a single organ-
ism or group of organisms.
Benchmarks and System Requirements
De-MetaST-BLAST has been developed for the long-term
support (LTS) Ubuntu operating systems 10.04 LTS and 12.04
LTS. While De-MetaST does not make use of multi-core
processors, BLAST maintains that capability. Benchmarks were
performed on an Intel i7-2600 processor (3.4 GHz quad-core, 8-
thread) desktop using the developed degenerate boxB primer set
against the Waseca Farm Soil metagenome (AAFX01000000)
. This search took approximately 11.7 s (Table 2). When the
database size was artificially and incrementally increased up to
five-fold (772 Mb) by replication of the original dataset, the
processing time remained ,1 min. Furthermore, to determine the
effect of increased numbers of positive hits on run time, the
libraries were seeded with additional sequences containing the
target. Doubling of targets within the databases had no effect on
run time (Table 2). In contrast to the relatively rapid processing
speed of De-MetaST, implementation of the BLAST function can
add significant processing time to the process, particularly if a local
custom database is used. As an example, for the initial benchmark
search against the locally installed Farm Soil metagenome that
recovered two hits, the BLASTx function added 39.3 s using two
threads. Thus, computational requirements and processing speed
are primarily dictated by BLAST. When BLAST is performed
remotely–the default setting (see below) –the return time is
dependent upon availability and processing speeds of the NCBI
Both De-MetaST and De-MetaST-BLAST can be run on any
operating system with a C++ compiler (e.g., standard Windows and
Mac OS). However, users would need to ensure the BLAST
installation is compatible with their processor.
Availability of De-MetaST-BLAST
The De-MetaST package and the De-MetaST-BLAST wrapper
are made freely available at http://sourceforge.net/p/de-metast-
blast/and http://code.google.com/p/de-metast-blast/. These files
are also provided as supplemental information to this publication
Table 1. boxB and 16S rRNA gene in silico amplicons identified in representative metagenomes using De-MetaST-BLAST.
CAMERA Metagenome Database Queried
boxB in silico
16S rRNA gene in
Number of Reads
dideoxysequencing (Sanger) and
dideoxysequencing (Sanger) and
aThe primers boxB171F (59CARGGNGAYACNGARCC39) and boxB265R (59YTTNCCRTCNCKRTCNGT39) were used to target an approximately 300 bp region of boxB.
bUnique reads were identified using MOTHUR (v.1.27.0) .
cThe primers 358f (59CCTACGGGAGGCAGCAG39) and 517r (59ATTACCGCGGCTGCTGG39)  were used to target an approximately 190 bp amplicon in the 16S rRNA gene.
dAverage read length was estimated by dividing the database size by number of reads. The AntarcticaAquatic database is dominated by pyrosequencing derived reads (98% of all reads), while the GOS dataset is dominated by
Sanger derived reads; the exact distribution for GOS reads is not available.
De-MetaST-BLAST: A Primer Validation Tool
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(File S1 and File S2). Along with the program, screencast tutorial
videos describe how to install the necessary programs as well as
implement the software package with the example dataset
provided. The De-MetaST package is self-contained and has no
external dependencies, except a C++ compiler, such as g++. De-
MetaST-BLAST requires a local BLAST+ suite installation that
supports direct query of the NCBI nr protein database using NCBI
servers via the –remote option. However, the program can also be
configured to query a custom local database. Both approaches are
described in tutorial videos provided. Installation of the De-
MetaST program is estimated at 5 min, whereas installation of the
BLAST+ suite is estimated to take 3 min, excluding download and
extraction times, which are dependent on the user’s internet speed
and processing power.
It was recently predicted that the increasing amounts of
metagenome sequences will likely serve as a valuable resource in
evaluation of the coverage and specificity of previously developed
primer sets . De-MetaST-BLAST will provide users with
a useful tool in such evaluations. De-MetaST is designed to
provide in silico amplicons generated by user defined degenerate
Figure 3. Example of De-MetaST-BLAST output. Text within the box denotes the spreadsheet output for a boxB primer set search against the
WASECA Farm Soil Metagenome (AAFX01000000)  that recovers two in silico amplicons. Column descriptors are shown in color; select columns
have been truncated due to space constraints. For the ‘‘excision info’’ column, the first alphanumeric character reports the ‘‘hit’’ number within a read
(i.e. ‘‘1’’ indicates it is the first in silico amplicon found within a single read). The subsequent alphanumeric characters denote the primer orientation
yielding the amplicon (F=forward, R=reverse). Whether a unique read identifier is returned is contingent upon the database itself.
Table 2. Runtime duration of De-MetaST.
Database [Mbp]Hits Real Time [s]User Time [s]
1 206.11.41542 11.7 11.70.02
2 412.22.83094 23.5 23.4 0.05
3 618.3 4.24636 35.2 35.10.07
4 824.45.56188 47.647.50.10
5 1030.57.077210 58.6 58.50.12
1 206.11.4 1544 11.9 11.90.02
2 412.2 2.8309823.323.30.05
3 618.34.2 46312 35.635.5 0.08
4 824.4 5.5 61816 47.347.1 0.10
51030.5 7.0 772 2058.258.00.12
aThe datasets used for benchmarking were manipulations of the Waseca Farm Soil metagenome (AAFX01000000); the average sequence read length in these datasets is
De-MetaST-BLAST: A Primer Validation Tool
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primers found within a user defined nucleotide database. When
paired with BLAST, the program returns the most homologous
GenBank hits, which are useful in assessing the specificity of
degenerate primers. However, the program does not evaluate
PCR kinetics and efficiencies with degenerate primers. Thus, users
are encouraged to consult appropriate references on the use and
design of degenerate primers (e.g., [43–44]), including those that
discuss the merits of utilizing base analogs (e.g., inosine; ) that
can reduce the overall degeneracy of primers.
illustrated within the De-MetaST-BLAST wrapper.
Computational procedures of De-MetaST are
Archive containing the source code for De-MetaST.
Archive containing the source code for De-MetaST-
We thank Dr. Charles R. Budinoff for insightful discussions and Ashley M.
Frank, P. Jackson Gainer, and W. Nathan Cude for providing valuable
feedback on program installation and use.
Conceived and designed the experiments: CAG. Performed the experi-
ments: CAG TCE. Analyzed the data: CAG AB. Contributed reagents/
materials/analysis tools: AB. Wrote the paper: CAG SWW AB.
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