Appl Microbiol Biotechnol (2009) 81:1129–1139 DOI 10.1007/s00253-008-1715-8

APPLIED MICROBIAL AND CELL PHYSIOLOGY

Artificial plasmid engineered to simulate multiple biological threat agents Monica Carrera & Jose-Luis Sagripanti

Received: 10 July 2008 / Revised: 3 September 2008 / Accepted: 8 September 2008 / Published online: 16 October 2008 # Springer-Verlag 2008

Abstract The objective of this study was to develop a nonvirulent simulant to replace several virulent organisms during the development of detection and identification methods for biological threat agents. We identified and selected specific genes to detect Yersinia pestis, Francisella tularensis, Burkholderia mallei, Burkholderia pseudomallei, Rickettsia sp., Coxiella burnetii, Brucella sp., enterohemorrhagic Escherichia coli O157:H7, Bacillus anthracis, and variola (smallpox) virus. We then designed and engineered a non-infectious simulant that included the nucleic-acid signature of each microorganism in a single chimerical molecule. Here, we reported an approach that by direct (de novo) chemical synthesis permitted the production of a single chimerical construct 2,040bp long that included the nucleic-acid signature of the bacterial and viral biological threat agents listed above without requiring access to these agents. Sequences corresponding to each one of the biological agents in the synthetic simulant were amplified by PCR, resulting in amplicons of the expected length, of similar intensity, and without any detectable unspecific products. The novel simulant described here could reduce the need for infectious agents in the development of detection and diagnostic methods and should also be useful as a non-virulent positive control in nucleic-acid-based tests against biological threat agents.

M. Carrera : J.-L. Sagripanti (*) Edgewood Chemical Biological Center, Research Development and Engineering Command US Army, AMSRD-ECB-RT, Aberdeen Proving Ground, Aberdeen, MD 21010-5424, USA e-mail: [email protected]

Keywords Threat agents . Bioinformatics . PCR . Multiplex . Bacillus anthracis . Yersinia pestis . Coxiellla burnetii . Brucella . Francisella tularensis . Enterohemorrhagic E. coli O157:H7 . Burkholderia mallei . Burkholderia pseudomallei . Variola . Smallpox

Introduction Nucleic-acid-based technologies are a mainstay in the strategy to detect and identify biological threat agents. However, the improvement in technology to detect and identify threat agents is hindered by the need to simultaneously address many potential targets and by the working risk posed by the agent’s high virulence. We initiated this study in an attempt to replace several virulent agents posing the highest biological threat with a single non-virulent simulant that could be used in the development of technology. Francisella tularensis, one of the most infectious pathogens and the etiological agent of tularemia, has been detected by PCR assays as reported by Long et al. (1993). PCR methods are also available to detect the two members of the Burkholderia genus with potential for bio-warfare, Burkholderia mallei (the etiologic agent of glanders) and Burkholderia pseudomallei (causative agent of melioidosis; Bauernfeind et al. 1998). PCR methods to detect Brucella species and Rickettsia have been described (Matar et al. 1996; Debeaumont et al. 2005; Tzianabos et al. 1989). Molecular methods to detect Coxiella burnetii and enterohemorrhagic Escherichia coli O157:H7 have been reported (Stein and Raoult 1992; Sharma and DeanNystrom 2003). Various PCR approaches have been described to detect variola virus, which causes smallpox (Espy et al. 2002; Fedele 2006).

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Several PCR methods have been reported for the detection of Bacillus anthracis, the etiological agent of anthrax (Carl et al. 1992; Makino et al. 1993), including a multiplex PCR that identified virulent and avirulent strains of B. anthracis (Ramisse et al. 1996). PCR assays to detect Yersinia pestis, the causative agent of “plague”, have been developed for diagnostic purposes (Norkina et al. 1994; Campbell el al. 1993, Loïez et al. 2003). A rapid and highly specific real-time PCR has been described for detection of multiple locus in Y. pestis (Tomaso et al. 2003). Using nucleic acids from infectious bio-threat agents as positive controls for testing is demanding due to the restrictions in handling and producing these organisms. The use of heat or radiation-inactivated organisms (or their nucleic acids) in method development still requires the production of virulent microorganisms at high risk and cost. Particularly, development of multiplex PCR methods has been hindered by the nearly insurmountable logistic and economic difficulties that involve producing a number of different virulent bacteria and viruses, isolating and characterizing them under adequate bio-containment, and preparing a representative control of each agent for evaluation of the testing method. In addition, biological simulants generally used in the development of countermeasures in biodefense [Bacillus athrophaeus (known before as Bacillus globigii), Pantoea agglomerans (known previously as Erwinia herbicola), and phage MS2 (O’Connell et al. 2006)] are particularly inadequate to evaluate specificity and sensitivity of nucleic-acid-based technologies, because these simulants do not share nucleic-acid targets with any threat agent. Thus, although several method are available (as listed above), identification of biological threat agents is hindered by the lack of a simulant to be used in the development of advanced detection systems and subsequently used as a non-infectious positive control during testing. A nucleic-acid simulant for threat agents was previously reported, consisting of sequences that correspond to several threat agents distributed among three plasmids (Charrel et al. 2004). These plasmids were constructed by successive PCR amplifications of the desired sequences followed by T4 ligation. Our goal was to develop a simulant that included specific sequences of DNA biological threat agents to be represented in only one plasmid molecule. In addition, we explored the possibility of such a multi-agent simulant being designed and engineered more easily by direct (de novo) chemical synthesis than by sequential ligations of purified PCR products. We report here an approach that allowed the production of a single chimerical construct that included the nucleic-acid signature of bacterial and viral biological threat agents without requiring access to these agents.

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Materials and methods The genomes of many of the biological threat agents are in the public domain. All genomes used in this work were downloaded from NCBI (National Center for Biotechnology Information, http://www.ncbi.nlm.nih.gov). The Basic Local Alignment Search Tool (BLAST, http://www.ncbi. nlm.nih.gov/BLAST), which compares query nucleotide sequences to sequences in databases and calculates the statistical significance of matches, was used to find similar genetic regions. The alignments of different strains were performed by ClustalX software (http://www.clustal.org). All potential primers were generated by FastPCR, a computer program for primer design (http://www.biocenter.helsinki.fi/bi/programs/ fastpcr.htm). We developed several scripts in Perl language to facilitate the analysis of the considerable amount of information that we generated during whole genome comparisons. Perl is a programming language that facilitates manipulation of strings (a set of consecutive characters) and has several modules specific for biological information handling (http://www.bioperl.org). Once design and in silico testing was completed, the DNA simulant was synthesized and cloned in the SacI/XhoI site in pBluescript II SK (+) by Celtek Bioscience (Nashville, TN, USA). TaqDNA Polymerase and restriction enzymes BamH1, HindIII, EcoRI, SamI and the 4-CORE® Buffer Pack were purchased from Promega Corporation (Madison, WI, USA). The 4-CORE® Buffer Pack contains convenient aliquots of proprietary Promega Restriction Enzyme 10× Buffers named A, B, C, and D by the manufacturer. We used these buffers, since most Promega restriction enzymes have optimal activity in one of these four proprietary buffers. All primers were purchased from Alpha DNA (Montreal, Quebec, Canada). PCR assays were performed using PCR Master mix (Promega, cat # M7502, Madison, WI, USA) in either 12.5or 25-μl volumes. PCR Master Mix, 2× is a premixed solution containing 50units/ml of Taq DNA polymerase supplied in a proprietary reaction buffer (pH8.5), 400μM dATP, 400μM dGTP, 400μM dCTP, 400μM dTTP, and 3mM MgCl2. Between 40 and 100pg of target DNA (synthetic simulant digested with BamH1) was added to each reaction as well as primers at the concentration indicated in the text. PCR was performed in a GeneAmp PCR System 9600 thermal cycler (PE Applied Biosystems, Foster City, CA, USA) under the following cycling conditions: denaturation at 94°C for 15min followed by 30cycles consisting of 94°C denaturation for 30s, 60°C annealing for 20s, and 72°C extension for 30s. A final 30-min extension was performed

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Table 1 Genome list and access numbers of microorganisms used in this work Genome (1)

Access Size (kb) Gene (4) numbers (2) (3)

Bacillus anthracis st. Ames B. anthracis st. 0581 “Ames ancestor” “R”

NC_003997

5,227

NC_007322 NC_007323

181 94

B. anthracis st. Sterne

NC_007530 NC_005945

5,227 5,228

B. anthracis st. Pasteur

NC_001496 NC_002146

181 96

NC_003909 NC_005707 NC_004722 NC_003131 NC_003132 NC_003134 NC_003143 Y. pestis KIM NC_004088 NC_004838 Y. pestis 91001 NC_005810 NC_005813 NC_005814 NC_005815 NC_005816 Yersinia pseudotuberculosis NC_006153 NC_006154 NC_006155 Francisella tularensis “R” NC_006570 Burkholderia mallei “R” NC_006348

5,224 208 5,411 70 9 96 4,653 4,600 100 4,595 70 21 17 9 68 27 4,744 1,892 3,510

NC_006349 NC_006350 NC_006351 NC_007650 NC_007651 NC_003103 NC_007109 NC_007110 NC_007111 NC_000963 NC_006142 NC_002971

2,325 4,074 3,173 2,914 3,809 1,268 1,485 62 39 1,111 1,111 1,995

NC_006932 NC_006933 NC_007618 NC_007624 NC_003317 NC_003318 NC_004310 NC_004311 NC_002127 NC_002128 NC_002695

2,124 1,162 2,121 1,156 2,117 1,177 2,107 1,207 3 92 5,498

NC_002655 NC_000913

5,528 4,639

Bacillus cereus ATCC 10987 B. cereus ATCC 14579 Yersinia pestis CO92 “R”

Burkholderia pseudomallei “R” Burkholderia thailandensis Rickettsia conorii Rickettsia felis

Rickettsia prowazekii “R” Rickettsia typhi Coxiella burnetii “R” Brucella abortus strain 9-941 B. abortus strain 2308 Brucella melitensis “R” Brucella suis strain 1330 Escherichia coli O157:H7 “R”

E. coli O157:H7 EDL933 E. coli K12

Location (5) Description (6)

References

Read et al. (2003) pag CapB

pXO1 pXO2

Protective antigen Capsule biosynthesis protein capb, (pxo2-58) Brettin et al. (2004, unpublished) Okinaka et al. (1999–2) Okinaka et al. (1999, direct submission) Rasko et al. (2004) Ivanova et al. (2003) Parkhill et al. (2001)

irp1

Chr

Y.bactin biosynthetic protein Deng et al. (2002) Lindler et al. (1998) Song et al. (2004)

Chain et al. (2004)

capB wcbQ

Chr ChrI

Capsule biosynthesis protein capB Larsson et al. (2005) Putative capsular polysaccharide Nierman et al. (2004) biosynthesis protein WcbQ Holden et al. (2004) Kim et al. (2005) Ogata et al. (2001) Ogata et al. (2005)

RP293

Chr

VIRD4 PROTEIN (virD4)

CBU1551

Chr

Dinucleoside polyphosphate hydrolase

Andersson et al. (1998) McLeod et al. (2004) Paulsen et al. (2003) Halling et al. (2005) Chain et al. (2005)

BMEI1877 Chr #1

HEMOLYSIN III

DelVecchio et al. (2002) Paulsen et al. (2002) Makino et al. (1998)

ECs0540

Chr

Putative outer membrane transport protein Perna et al. (2001) Blattner et al. (1997)

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Table 1 (continued) Genome (1)

Access Size (kb) Gene (4) numbers (2) (3)

Variola major reference “R” NC_001611

185

Variola minor

Y16780

186

V. major Bangladesh 1975

L22579

186

Location (5) Description (6)

G4R

References

G4R protein

Shchelkunov et al. (1994) Shchelkunov, S.N. direct submission Massung et al. (1993)

(1) All genomes (including plasmid genomes) were downloaded from NCBI (National Center for Biotechnology Information; http://www.ncbi. nlm.nih.gov). The strain or species considered as representative of each threat agent group is indicated with an “R”. (2) Accession numbers correspond to NCBI (National Center for Biotechnology Information). (3) Genome sizes (in kilobase) were obtained from the respective reference indicated on the right column and correlated to the accession number in NCBI (National Center for Biotechnology Information). (4) and (5) Gene name and molecule location when known of the selected sequence for primer design, respectively. (6) Reported biological function

to avoid incomplete 3′ adenine nucleotide addition (+A peaks). After PCR amplification, the fluorescent products were mixed with 3 volume of Loading Buffer (5:1 Formamide/25mM EDTA pH8:00), mixed with 0.5 –l.0μl of GS 500 TAMRA size standard (16 ssDNA fragments of known size, Applied Biosystems) and then separated by 4.5% polyacrylamide 19:1 gel electrophoresis using an ABI Prism 377 automated sequencer (PE Applied Biosystems). All formulations and procedures were done following the recommendations of the ABI Prism 377 DNA Sequencer User’s Manual [Applied Biosystems Inc. GeneScan® Reference Guide: Chemistry Reference for ABI Prism® 377 Genetic Analyzer. (http://www.appliedbiosystems. com)]. Data Analysis was performed using the GeneScan 3.1.2 software (PE Applied Biosystems).

R G (Brucella group)

ALL-G

(Brucella melitensis 3198 genes)

Threat agents database except "G" (excluding Brucella)

BLAST (R) versus (ALL-G)

DESCARTED genes (639 genes)

G database [G-R]

First selection

Genes with NO Hits (NO) (2559 genes)

Results

BLAST ( NO ) versus ( G-R) Search and download the available complete genome of each agent All genomes available in GeneBank (March 2005) for each target organism were downloaded and analyzed in this study. The 54 genome sequences used to make databases in this study are listed in Table 1. As expected, the level of variability in genome sequences obtained among closely related species or strains was significantly smaller than the variability found between less related species. For this reason, we found it useful to select one species or strain as a “representative” of the group for interspecies comparison (see Table 1). Database and genome comparison between microorganisms For each particular threat agent, our goal was to identify specific gene sequences having two characteristics: (a) to be

Not Conserved genes DESCARTED

List of selected genes for every threat agent

Second Selection

Conserved genes SELECTED (2151 genes)

Fig. 1 Gene analysis. Scheme representing the approach used to select genes of threat organisms. G represents a particular group of threat agents. R corresponds to the representative strain within a particular group. In parentheses is Brucella used as an example to illustrate the procedure. BLAST was the program used for comparison

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producing none, one, two, three, or more hits with the corresponding ALL-G database. A hit was considered a matching sequence between the “representative agent” and any of the genomes in the ALL-G database (with an error lower than 0.001). The BLAST parameters were selected to detect alignments of at least 20–25 nucleotides. All genes that had some degree of similarity (one hit or more) were discarded, and the genes of G with no hits against ALL-G were selected (genes labeled NO in Fig. 1). These genes containing sequences specific for each threat organism were thus (negatively) selected for further analysis (first selection in Fig. 1). To select conserved genes within the same species groups, a second (BLAST) comparison was performed. This second alignment was done by creating an agentspecific database that included the complete genomes of all strains or species within a group listed in Table 1 except the representative agent. Using the example in Fig. 1, the genes of B. melitensis (representative genome of the Brucella group, “R” in Table 1) that did not match any other genome in the first comparison (NO) were compared against a new database [called G-R (G minus R)] consisting of the genomes of all strains in the Brucella

absent in the other species listed in Table 1 and (b) to be conserved within all the strains of the particular threat agent or among the species belonging to the agent’s group. Each threat genome was compared against all the other genomes listed in Table 1 using BLAST as described in the “Materials and methods”. Figure 1 shows a scheme representing all the steps of the procedure performed for each individual gene using Brucella sp. as an example. As shown on Fig. 1, BLAST databases were created with all species genomes in Table 1 excluding the genomes of one of the species group at a time. In the example shown in Fig. 1, Brucella melitensis is compared to all other species [B. anthracis, Yersinia, Rickettsia, Coxiella, Francicella, E. coli, Burkholderia, and variola virus; in a database labeled as ALL-G (ALL minus G) in Fig. 1], but not to the other Brucella strains (labeled “G”). Thus, there were nine different ALL-G databases, each with all genomes except those of a particular group. The representative agent selected as indicated above and compared to all the rest of the species in a group (B. melitensis in the example) is labeled “R” (for “reference”) in Fig. 1. After the initial BLAST [BLAST (R) versus (ALL-G) in Fig. 1], the resulting genes were grouped according to

Table 2 Primer sequence, quality index, and expected PCR products for all selected agents used in the design and construction of the simulant and in the threat agent Genome

Francisella Burkholderia Rickettsia Coxiella burnetti Brucella Escherichia Variola Bacillus anthracis pXO1 B. anthracis pXO2 Yersinia

Sequence

agccacttttgcaatcgctgtgtgag 5′ HEX agctgcgattagttctgagcctcggt 5′ TET tgccattgccctgtcatttgccgcag acaactgactgaacagactcaggtcg gcttattttagaggttatagagttcg 5′ FAM acttcttgaggtaaaagtaaagctct 5′ HEX cccaacgaaaccttgcgtgaggca acgtctcgcttaaactcaacgacgtgg cgatggcgtcatccatgtgctgggtg 5′ TETagtttgagcatgatgccgacgaaagc gcaggcctgaactcatcgtcggatga 5′ FAM tcatcccaatacgagcggtcgctgg 5′ HEX gcagcaccgtatacaccacccaatg acgtctccaacagacgtgtgtccggat 5′ TET tggatttcaagttgtactggaccgat tgtcacggtctggaaccgtaggtcc 5′ FAM tgctgaccaatctaagcctgcgt agcaaactgctcagtacgatcaac 5′ HEX acccacctcattggctatggcggcgt tcacgcgggatgtgatactccggcg

Length (1)

26 26 26 26 26 26 25 26 26 26 26 26 26 26 24 26 26 26 26 26

Tm (2)

63 64 67 61 52 55 65 60 66 62 65 66 64 65 61 62 60 66 68 67

Quality (3)

112 136 115 101 80 79 116 107 142 107 120 136 122 112 101 117 85 118 132 144

Ta PCR (2)

PCR product (bp) In simulant

In threat agent

60

100

230

65

115

260

57

130

290

61

145

310

65

160

330

66

175

350

62

190

380

59

205

150

60

220

160

66

235

200

(1) Primers of preferable length of 26 bp were selected. (2) The selection of primers has in consideration similar Ta and Tm to improve multiplex assays. (3) The predicted efficiency of primers was determined by FAST PCR software (see “Materials and methods”). High quality values should provide high amplification efficiency. Maximal quality values for primers 24–26 nucleotides in length are near 150

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group except that of B. melitensis (R). In this second BLAST, the representative agent (R) was used as a query for each corresponding G–R database. The genes conserved within the different strains of an agent group were thus positively selected and considered agent specific (second selection in Fig. 1). Our approach involving a two-step analysis (consisting in a negative selection followed by positive selection)

defined a set of genes conserved within closely related species or group (e.g., among all B. anthracis or among all Brucella) but with no sequence similarity with any of the others of the species or groups listed in Table 1. To avoid cross reactivity with any known organism and to assure specificity, another selection step using BLAST against Genebank was performed during primer design (see below the section on “Selection of specific primer pairs”).

Primer forward

Primer reverse

DNA fragment used for design

Deleted bases

Amplified fragment in genomes

1 3

Burkholderia group

6

5

Rickettsia group

4

7

Coxiella burnetti

9

Brucella group

10

a

8

Francisella group

2

Variola virus pXO1 Bacillus anthracis pXO2 Bacillus anthracis Yersinia group

Intrafragment sites

Escherichia coli group

Probes

Interfragment sites

Fragment in Simulant 100 bp

b

c

Fig. 2 Scheme of the designed chimerical molecule. A Yellow segments represent the genomic sequence of each threat agent. Specific sequences within the yellow segment that were selected for primer design appear in green. Deletion of nucleotides in the simulant (diagonal bars) gives a smaller amplified fragment. Ten nucleotides at each side of the primers were conserved in the simulant (blue segments) permitting the design of additional primers. B The organization of ten specific sequences (blue segments) corresponding to nine threat agents

(two for B. anthracis). Interfragment sites in red contain the specific sites for the enzymes BamHI (–GGATCC–) and HindIII (–AAGCTT–), and intrafragment sites in yellow contain the specific sites for enzymes (EcoRI –GAATTC– and SmaI –CCCGGG–). This chimerical construction was inserted in the pBluescript SK plasmid between XhoI and SacI restriction sites, as shown in C. Only interfragment BamHI restriction sites are shown in C. Grey bars represent specific sequences to be used as probes in detection assays

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To ensure that our simulant would reflect the virulence of biological threat agents, we selected among the conserved genes identified above in each individual species those genes that were associated with pathogenicity according to the studies referenced in Table 1. For example, we selected conserved pathogenic genes present in B. mallei and B. pseudomallei and absent in Burkholderia thailandensis, which is an avirulent species (Inglis and Sagripanti 2006). Sizes selection After identifying specific target sequences in each selected microorganism, we established in silico the size of each DNA fragment that would result from PCR amplification. In addition, a DNA chimera with specific sequences for each microbial target was designed to produce PCR amplicons of sizes different than the fragments resulting from amplification of the original pathogenic genome. This designed difference between PCR amplicons from the engineered chimera and from the actual targets permitted the identification of any false positives derived from potential contamination of samples with the chimerical simulant. Table 2 describes the primers and the sizes of the products to be obtained by PCR amplification of the gene in the infectious agent or from the fragment engineered in the simulant. The indicated sizes and specific selected sequences were utilized as parameters for primer design using the FastPCR software. Two fragment sizes corresponding to each plasmid in B. anthracis were selected, because the absence of any plasmid in B. anthracis considerably reduces pathogenicity (Dixon et al. 1999).

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Selection of specific primer pairs Possible, yet unspecific, primers (able to bind to nonrelated genomes in Table 1) were discarded by a preselection step consisting in the BLAST of designed primers against the whole contents of GeneBank. All primers were subjected to an in silico PCR prediction using FastPCR. We made a list of primers (within the selected genes) that showed 100% similarities with the target genome and a similarity lower than 80% with any other genome in GeneBank by using a Perl script that we specifically designed for this purpose. Those primers that showed more than 80% similarity and five matches in the 3′ end of the last seven bases generating an amplified fragment in any genome on GeneBank were discarded.

Primer design The whole gene sequences of the selected bacterium or smallpox virus were used for primer design. Primers 22–26 nucleotides long were designed with an annealing temperature above 55°C. The FastPCR software was used as indicated in the “Materials and methods” to determine PCR products of the desired length shown in Table 2. The amplified size parameter used in FastPCR was within a range of ±20 nucleotides of the selected sequence in order to generate a more extensive list of potential primers. All the remaining parameters used on FastPCR were the software default settings. All the possible primers were predicted for each of the DNA sequences selected. Then, a list was compiled with all the possible “primer pairs” able to generate an amplified DNA fragment of the desired length. A file containing all the primers and primer pairs was created for each selected gene as output from the FastPCR analysis. (Data not shown.)

Fig. 3 Expansion of the chimerical molecule as demonstrated by 2% agarose-gel electrophoresis of the M13-amplified simulant after enzymatic digestion. First lane to the left, SIM-M13 corresponds to the amplified simulant using the M13 Fw and Rev primers specific to Bluescript plasmid. HindIII, BamH1, EcoR1, and SmaI lanes correspond to identical SIM-M13 DNA samples after being digested with HindIII, BamH1, EcoR1 and SmaI, respectively. Restriction enzyme digestions were performed using 1 U/μl of enzyme at 37 °C for 2 h except for Sma1, in which the incubation was done at 25 °C. LMWM low molecular weight marker

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additional primers could be designed with a flexibility approximately 30bp at each side of the selected sequence. This made possible replacement by a contiguous set of primers (see Fig. 2a) when a chosen primer set interacted with the others in the multiplex PCR detection assay. We added two restriction sites (EcoRI –GAATTC– and SmaI –CCCGGG–) in the middle of the sequence of each fragment inserted in the chimerical simulant. These two enzymes did not cut any of the amplified fragments (except for an EcoRI site in the Rickettsia group of genomes). The restriction fragments were inserted to allow for the identification of amplicon origin, whether from microorganisms or from simulant. Thus, only the amplicons resulting by amplification of the simulant (which contains the restriction sites) produced digesting fragments visible by electrophoresis analysis.

There were still a considerable number of potentially specific primer pairs. Primer pairs for each genome fragment were further selected to be (1) preferably 26bp long, (2) high quality values, (3) similar annealing temperature, and (4) theoretical amplified fragment size close to that indicated in Table 2. The sequence and quality of each designed primer is shown in Table 2. Each primer set (consisting of different combinations of primer pairs against each agent) was then tested by in silico multiplex PCR against the corresponding microbial genome. We selected those primer sets where in silico generated only fragments of the expected size without producing unspecific products. Design of fragment for each genome After obtaining the primers and amplified fragments for each genome, the chimerical molecule to be used as simulant in PCR reactions was designed. The length of simulant amplified fragments differed from those present in or amplified from actual genomes, as detailed in Table 2. The fragments from the simulant of the sizes indicated in Table 2 were obtained by deleting bases in the middle of the sequences to be amplified. Flanking sequences (10-base long) present in the original genome were added at the sides of the primer hybridization sites in the selected primers. In this way,

Chimera design and assembly The selected fragments corresponding to various threat agents were connected in a single chimerical molecule. Two additional restriction sites were added between each of the fragments in the chimera to allow performing a digestion step before the amplification process. This digestion was necessary to prevent amplifying fragments longer than

Variola 190 bp

Francisella 100 bp Coxiella 145 bp

Yersinia 235 bp

Brucella 160 bp Burkholderia 115 bp

B. anthracis pXO1 205 bp

Yersinia B. anthracis pXO2 B. anthracis pXO1 Variola

Rickettsia Escherichia 130 bp 175 bp

Escherichia Brucella

B. anthracis pXO2 220 bp

Coxiella Rickettsia Burkholderia Francisella

Fig. 4 Amplification of individual fragments. Electrophoresis of individual amplified fragments performed on an ABI 377 sequencer analyzer. Left panel represents the reconstructed gel image showing the amplified fragments with the color given by the corresponding fluorescent label primer used. The right panels correspond to the electropherogram representation of the same data grouped by fluorescence-labeled primers. Upper right panel Fragments amplified using HEX (yellow)-labeled primers. Middle right panel TET (green)-

labeled primers. Lower right panel FAM (blue)-labeled primers. DNA fragments with a known molecular weight labeled with TAMRA (red) were included as an internal standard. The fragment sizes were estimated from their electrophoretic mobility through the gel relative to the internal size standard, as indicated by GeneScan 2.1 analysis software (Perkin-Elmer, Foster City, CA, USA). The accuracy of the size estimates, expressed to a fraction of a nucleotide unit, is specific to the electrophoretic separation conditions used

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expected, since the amplification of two consecutives fragments by primers at the farthest extremes could possibly confound results. Thus, the specific sites for the enzymes BamHI (–GGATCC–) and HindIII (–AAGCTT–) were introduced between each fragment and also at the beginning and end of the chimerical molecule as shown schematically in Fig. 2b. Characteristics of the synthesized chimera The plasmid vector used in the construction was pBluescript II SK (+), and the cloning site for the simulant sequence was the SacI/XhoI site. The construct map showing all the restriction enzyme sites introduced in the molecule to allow multiplex amplification and elimination of possible false positives due to contamination with the plasmid is depicted in Fig. 2. Amplification of simulant and restriction enzyme digestion Large amounts of DNA were generated without having to grow considerable amounts of plasmid DNA by amplification of the insert with M13 universal primers (Fig. 3). The presence and size of each sequence corresponding to the different microbial agents were confirmed by digestion with restriction enzymes and subsequent agarose-gel-electrophoresis analysis. The results shown in Fig. 3 demonstrate that this procedure generates ten fragments of the expected sizes. Amplification of individual fragments Sequences corresponding to each biological agent were independently amplified by PCR assays using the conditions described in the “Materials and methods”. Each product corresponding to each one of the biological agents under study was amplified with the expected length (as indicated in Table 2) and without any detectable unspecific amplification products as shown by Fig. 4. The similar intensity of the bands indicates that the relative amplification rate and, therefore, representation of sequences in our synthetic simulant are comparable for every threat agent.

Discussion The increasing interest in developing methods to detect and identify bio threat agents is hindered by the difficulty involved in working with highly virulent organisms. In this study, we describe computational analysis and selection of target sequences, design and engineering of a novel chimerical molecule, as well as experimental data demonstrating that signatures from 12 threat agents can be amplified from a single chimerical simulant.

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We present a simplified technique (using direct chemical synthesis instead of amplification of DNA threat agents followed by ligation) to include in a single molecule sequences of different lengths corresponding to a variety of microbial agents. The microbial agents were represented in the simulant by sequences of different length, and the insertion of restriction enzyme sites further assisted in the identification of individual sequences. Bioinformatics analysis followed by chemical de novo synthesis of the simulant reduced the costs and bio-hazards associated with the manipulation of threat agents. The design and synthesis of the intended simulant was confirmed by analysis of restriction-enzyme-digested products and by PCR amplification of sequences specific for each targeted organism. The multiplex simulant molecule engineered here could be used instead of virulent organisms to evaluate the performance of nucleic-acid-based bio-detectors and diagnostic products of interest in biodefense. Thus, this simulant would reduce the need to use individual bio-threat agents or their DNA as target during methods development or as positive controls during the actual testing of clinical specimens or environmental samples. A single simulant should be useful in comparing the performance of a variety of technologies currently used or envisioned of potential use in biodefense that target single or multiple biological agents. Evaluation and comparison of a variety of diagnostics and biological detectors could be done with the simulant described here without exposing testers or trainees to pathogenic biological agents. It is expected that the use of this simulant will reduce the cost and risk of developing and testing technologies related to clinical diagnosis of and military countermeasures against the pathogens included in this work. Safer, cheaper, and faster development and evaluation of technology should promote increased reliability of biological diagnostics and detectors. Better controls and improved technology should reduce the rate of false positives in clinical samples and of military false alarms, which degrade operational capabilities by unnecessary masking and gowning. Acknowledgment This work was supported by the In-House Laboratory Independent Research (ILIR) funds from the Research and Technology Directorate, Edgewood Chemical Biological Center, Research Development and Engineering Command, US Army.

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