CASE CLOSED … what really happened in the 2001 anthrax attacks?

* The June 2, 2010 National Academy of Sciences meeting is closed but you can email (skendall@nas.edu) with any questions … The meeting is closed because the committee is drafting its report

Posted by DXer on June 1, 2010

.

The FBI’s case against Dr. Ivins is bogus: no evidence, no witnesses, an impossible timeline, science that proves innocence instead of guilt. So what really happened? And why? The “fictional” scenario in my novel CASE CLOSED has been judged by many readers, including a highly respected official in the U.S. Intelligence Community, as “quite plausible.”

* buy CASE CLOSED at amazon *

.

******

I sent the following email to skendall@nas.edu on 6/1/10 …

Can you please explain why this meeting is closed?

Can you tell me the agenda for the meeting?

When is the next scheduled OPEN session?

******

Here is the answer …

The meeting is closed because the committee is drafting its report.

No open meeting sessions are currently scheduled.

******


******

11 Responses to “* The June 2, 2010 National Academy of Sciences meeting is closed but you can email (skendall@nas.edu) with any questions … The meeting is closed because the committee is drafting its report”

  1. DXer said

    Food Microbiol. 2010 Aug;27(5):661-6. Epub 2010 Mar 9.
    Hydrophobic properties and extraction of Bacillus anthracis spores from liquid foods.
    Leishman ON, Labuza TP, Diez-Gonzalez F.
    Department of Food Science and Nutrition, University of Minnesota, 1334 Eckles Avenue, St. Paul, MN 55108, USA.
    Abstract
    The objectives of this study were to characterize the hydrophobic properties of three strains of Bacillus anthracis using the microbial adherence to hydrocarbons (MATH) assay and determine the recovery of spores by hexadecane extraction from water, milk and orange juice using a modified version of this assay. In water mixtures, the hydrophobicity of B. anthracis spores ranged from 5 to 80% as the concentration of hexadecane and the mixing time increased. Two of the three strains showed significantly different hydrophobicity values. Increased pre-incubation temperature of the spore suspension had inconsistent effects on hydrophobicity across the three strains. The hydrophobicity of spores did not change significantly during storage at 4 degrees C. However, recovery of spores in the hexadecane fraction from aqueous mixtures was always less than 5% even at conditions in which the hydrophobicity values were greater than 40%. The recovery of spores in the hexadecane fraction increased to almost 20% when the hexadecane was mixed with milk or orange juice, although the majority of spores remained in the aqueous phase. The B. anthracis spores were relatively hydrophobic according to the MATH assay, but this test was not a good predictor of the partitioning of B. anthracis spores to hexadecane. The separation of B. anthracis from food matrices using hexadecane extraction was ineffective. Although the modified MATH assay was not able to efficiently extract B. anthracis from various food media, development of methods for rapid concentration and separation of this and other select agents from food remains vital to food defense. Copyright 2010 Elsevier Ltd. All rights reserved.

    See also

    J Food Prot. 2008 Mar;71(3):473-8.
    Decontamination of fluid milk containing Bacillus spores using commercial household products.
    Black DG, Taylor TM, Kerr HJ, Padhi S, Montville TJ, Davidson PM.
    Department of Food Science & Technology, University of Tennessee, 2605 River Drive, Knoxville, Tennessee 37996, USA.
    Abstract
    Although commercial sanitizers can inactivate bacterial spores in food processing environments, relatively little data exist as to the decontamination of products and surfaces by consumers using commercial household products. Should a large scale bioterrorism incident occur in which consumer food products were contaminated with a pathogenic sporeformer such as Bacillus anthracis, there may be a need to decontaminate these products before disposal as liquid or solid waste. Studies were conducted to test the efficacy of commercial household products for inactivating spores of Bacillus cereus (used as a surrogate for B. anthracis) in vitro and in fluid milk. Validation of the resistance of the B. cereus spores was confirmed with B. anthracis spores. Fifteen commercial products, designed as either disinfectants or sanitizers or as potential sanitizers, were purchased from retail markets. Products selected had one of the following active compounds: NaOCl, HCl, H2O2, acetic acid, quaternary ammonium compounds, ammonium hydroxide, citric acid, isopropanol, NaOH, or pine oil. Compounds were diluted in water (in vitro) or in 2% fat fluid milk, and spores were exposed for up to 6 h. Products containing hypochlorite were most effective against B. cereus spores. Products containing HCl or H2O2 also reduced significant numbers of spores but at a slower rate. The resistance of spores of surrogate B. cereus strains to chlorine-containing compounds was similar to that of B. anthracis spores. Therefore, several household products on the market may be used to decontaminate fluid milk or similar food products contaminated by spores of B. anthracis.

    Comment: It expressly violates the hadiths to contaminate livestock or food or drink.

  2. DXer said

    On October 9, 2004, Dr. Ivins wrote:

    “We don’t have antifoam in the production procedure, and that may have an effect later on during the spray. I gave ___ some Tween-80 that is approved for human use and can be used in the aerosols (at a 0.1% final concentration) as an antifoam. I don’t have sufficient knowledge of the aerosol apparatus to comment. Beyond adding Tween-80 to the spores prior to spraying, I don’t know how to reduce foaming. Did the first spores we sent you for ___ this past spring also foam? I remember that ___ said that when ___ added some of the A-240 antifoam (that you use) to our spores, it impressed the spray efficiency by 5 to 10-fold.”

  3. DXer said

    Dr. Ivins wrote on October 26, 2004:

    “This is a complete mystery to me as to why the foaming/clumping happens. I’m sending (towards the end of November) 2 x 10e12 Ames spores to ____ for a _____ experiment I’ve been taking extra care in washing, and they don’t seem to be foaming.

    What happens when the cultures are grown without antifoam in the fermentor vessel? Meglumine was detected in our spores. Is antifoam detectable on the spores produced at ________ (If so, the residual antifoam may help prevent the foaming and clumping seen with the spores produced at USARMIID.)

    What I’d like to do here is change the cleaning/puriffying procedure a bit (substituting sucrose for Hypaque, for example) then see if that cuts down on spore clumping and foaming.”

  4. DXer said

    The NAS review of the science will have been seriously deficient if it does not review the FBI’s examination of the toner used to photocopy the anthrax letters. Dr. Bartick should be asked to testify about his important work. My source of intelligence says that the examination of the photocopy toner excludes the photocopy machine that Rachel Carlson Lieber and Kenneth Kohl, without basis, alleged was used by Dr. Ivins.

    For a recent journal article on the issue, see the May 2010

    Ablative analysis of black and colored toners using LA-ICP-TOF-MS for the forensic discrimination of photocopy and printer toners

    Szynkowska, M.I.a , Czerski, K.a , Paryjczak, T.a , Parczewski, A.b c

    a Institute of General and Ecological Chemistry, Technical University of Lodz, Zeromskiego 116, 90-924 Lodz, Poland
    b Department of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Cracow, Poland
    c Institute of Forensic Research, Westerplatte 9, 31-033 Cracow, Poland

    Abstract

    Photocopy and printer toners were analyzed using ICP-TOF-MS (inductively coupled plasma time-of-flight mass spectrometry) with laser ablation (LA). Isotopic analysis of black and colored toners allows identification and discrimination of covering materials from different producers. The results of 201 samples of black toners were analyzed according to the following chemometric methods: cluster analysis (CA) and principal component analysis (PCA). In addition, 23 samples of colored toners were tested. Chemometric manipulation of the elemental mass spectra obtained using the ‘Fingerprinting OptiMass 9500’ program showed an effective system for the rapid comparative analysis of unknown samples. Copyright © 2010 John Wiley & Sons, Ltd.

    Language of Original Document

    English

    Author Keywords

    Chemometric data handling; Inductively coupled plasma time-of-flight mass spectrometry (ICP-TOF-MS); Isotopic analysis; Laser ablation (LA); Toners

    Index Keywords

    Chemometric data; Chemometric data handling; Chemometric method; Chemometrices; Comparative analysis; Covering material; Elemental mass; Isotopic analysis; Printer toners; Time of flight mass spectrometry

    Engineering controlled terms: Chromatography; Cluster analysis; Data handling; Electromagnetic induction; Isotopes; Laser ablation; Laser applications; Mass spectrometers; Mass spectrometry; Photocopying; Photoresists; Principal component analysis; Printers (computer); Printing presses

    Engineering main heading: Inductively coupled plasma

    ——————————————————————————–

    Surface and Interface Analysis
    Volume 42, Issue 5, May 2010, Pages 429-437

  5. DXer said

    Justice Dept. Called Unready for W.M.D. Attack
    By ERIC SCHMITT
    Published: June 1, 2010
    WASHINGTON — The Justice Department’s inspector general has concluded that the department is not fully prepared to respond to a terrorist attack involving a weapon of mass destruction.

    In a report issued on Tuesday, the inspector general said that none of the law enforcement agencies within the department, other than the Federal Bureau of Investigation, had operational response plans in place to deal with such an attack.

    Other than F.B.I. specialists, the department’s staff receives little training on how to respond to a biological, chemical, nuclear or radiological attack; there is no central oversight plan in place for such a crisis; and the management of the department’s plan is “uncoordinated and fragmented,” the report determined.

    “The Department as a whole does not have policies or plans for responding to a W.M.D. incident,” the 61-page report concluded.

    The report did not address the role of other Federal agencies, such as the Defense and Homeland Security departments, that would also have important roles in dealing with any unconventional terrorist attack.

    The Justice Department said it largely agreed with the critique from its inspector general, Glenn A. Fine, but that it had made meaningful progress in correcting the shortfalls while the report was being compiled.

    James A. Baker, an associate deputy attorney general, wrote in a letter dated May 25 that the department largely embraced many of the inspector general’s recommendations. Mr. Baker wrote that one person in the office of the deputy attorney general would be selected in the next few weeks to oversee the department’s emergency response.

  6. DXer said

    Email for a copy of the May 24, 2010 presentation by Dr. Kotula and Dr. Michael at the
    Southeastern Microscopy Society Annual Meeting in Charleston.

    “Microanalysis and the FBI’s Amerithrax Investigation of the 2001 Anthrax Attacks”
    Paul G. Kotula and Joseph R. Michael, Sandia National Laboratories

    • DXer said

      Presentation addressed whether the mailed anthrax contained an additive “to make it disperse predictably.”

      Summary (without powerpoints)

      Microanalysis and the FBI’s Amerithrax Investigation of the 2001 Anthrax Attacks

      Paul G. Kotula and Joseph R. Michael Sandia National Laboratories, PO Box 5800, MS 0886, Albuquerque, NM, 87185-0886

      The Anthrax attacks of 2001 in the US killed 5, sickened 22 others and caused a significant disruption of mail and other government facilities. Although the attack materials were for the most part recovered (Bacillus Anthracis) in powder form in sealed envelopes, the US Federal Bureau of Investigation (FBI) was unprepared to perform the needed forensic analyses on these bio-weapon materials. In particular, it was identified that microanalysis from the micro- to nano-scale was a key missing piece of their capabilities. As a result, Sandia was asked to analyze the materials from the attacks by early 2002 and we reached our general conclusions within a few months. We also analyzed over 200 samples of B. anthracis between 2002 and 2008 in an attempt to discern the method of manufacture of the attack materials.

      This talk will describe Sandia’s involvement in the FBI’s investigation and in particular the power of microanalysis in answering several critical questions: Was the Bacillus Anthracis intentionally weaponized (i.e., contain an additive to make it disperse predictably) and were the materials from the attacks from the same source? In particular x-ray spectral imaging (in the SEM and STEM) combined with multivariate statistical analysis [1-3] were used to answer these questions. Specimen preparation was both by conventional microtomy and focused ion beam (FIB) sectioning of spore preparations. In addition, significant advances in analytical throughput were achieved by modification of a FE-SEM with an annular Si-drift detector with a solid angle of over 1 steradian. STEM in SEM was then performed with this new hybrid instrument in order to analyze large numbers of spores in a short time.
      References: [1] P.G. Kotula, M.R. Keenan and J. R. Michael, “Automated Analysis of SEM X-Ray Spectral Images: A Powerful New Microanalysis Tool,” Microsc. Microanal. 9, 1-17 (2003).
      [2] P.G. Kotula and M.R. Keenan, “Application of Multivariate Statistical Analysis to STEM X-Ray Spectral Images: Interfacial Analysis in Microelectronics,” Microsc. Microanal. 12, 538-544 (2006).
      [3] L.N. Brewer, J. A. Ohlhausen, P.G. Kotula, and J.R. Michael, “Forensic analysis of bioagents by X-ray and TOF-SIMS hyperspectral imaging,” Forensic Science International 179 98-106 (2008). Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United Stated Department of Energy’s (DOE) National Nuclear Security Administration (NNSA) under contract DE-AC0494AL85000.

  7. DXer said

    The NAS panel also has the benefit of a new study by FBI authors on obtaining intelligence about the production methods of Bacillus organisms in a forensic investigation.

    “When taken together, these analyses indicate that B. cereus spore samples grown in different media can be resolved with FAME profiling and that this may be a useful technique for providing intelligence about the production methods of Bacillus organisms in a forensic investigation.”

    Appl. Environ. Microbiol. doi:10.1128/AEM.02443-09

    Copyright (c) 2010, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved.

    Discrimination of Bacillus cereus T-strain Spores Grown on Different Media using Fatty Acid Methyl Ester (FAME) Profiles
    Christopher J. Ehrhardt, Vivian Chu, TeeCie Brown, Terrie L. Simmons,Brandon K. Swan, Jason Bannan, and James M. Robertson*
    Visiting Scientist, Federal Bureau of Investigation, Quantico, VA 22135; Counterterrorism and Forensic Science Research Unit, Federal Bureau of Investigation, Quantico, VA 22135; Department of Biochemistry and Molecular Biology, Oklahoma State University, Stillwater, OK, 74078; Marine Science Program & Department of Earth Science, University of California at Santa Barbara, Santa Barbara, CA 93106; Chemical and Biological Sciences Unit, FBI Laboratory Division, Quantico, VA 22135

    * To whom correspondence should be addressed. Email:james.m.robertson@ic.fbi.gov.

    Abstract
    The goal of this study was to determine if cellular Fatty Acid Methyl Ester (FAME) profiling can be used to distinguish among spore samples from a single species (Bacillus cereus T-strain) that were prepared on ten different medium formulations. To analyze profile differences and identify FAME biomarkers diagnostic for the chemical constituents in each sporulation medium, a variety of statistical techniques were used including non-metric multidimensional scaling (nMDS), analysis of similarities (ANOSIM), and discriminant function analysis (DFA).

    Results showed that one FAME biomarker, oleic acid (18:1 9c), was exclusively associated with spores grown on Columbia Agar supplemented with sheep blood, and was indicative of blood supplements that are present in the sporulation medium. For spores grown in other formulations, multivariate comparisons across several FAME biomarkers were required to discern profile differences. Clustering patterns in nMDS plots and R values from ANOSIM revealed that dissimilarities among FAME profiles were most pronounced when comparing spores grown with disparate sources of complex additives or protein supplements (R>0.8, p<<0.01), although other factors also contributed to FAME differences. DFA indicated that differentiation can be maximized with a targeted subset of FAME variables and the relative contributions of branched FAME biomarkers to group dissimilarities changed when different media were compared. When taken together, these analyses indicate that B. cereus spore samples grown in different media can be resolved with FAME profiling and that this may be a useful technique for providing intelligence about the production methods of Bacillus organisms in a forensic investigation.

    • DXer said

      Were the bloodhounds reacting to the smell of oleic acid at Denny’s?

    • DXer said

      As an excipient in pharmaceuticals, oleic acid is used as an emulsifying or solubilizing agent in aerosol products. One of the chief sources of oleic acid in foods is olive oil, perhaps one of the tastiest cooking oils. USAMRIID scientists were asked whether they had seen a bottle of olive oil.

      “Why is the FBI asking everyone if they have ever seen olive oil in one of the aerosol rooms?”

    • DXer said

      Note the probativeness of this FBI analysis to use of Tween 80. Now if only the compartmentalization of the Task Force had not prevented Jason Bannan from seeing the full picture.

      Applied and Environmental Microbiology, March 2010, p. 1902-1912, Vol. 76, No. 6
      0099-2240/10/$12.00+0 doi:10.1128/AEM.02443-09
      Copyright © 2010, American Society for Microbiology. All Rights Reserved.

      Use of Fatty Acid Methyl Ester Profiles for Discrimination of Bacillus cereus T-Strain Spores Grown on Different Media
      Christopher J. Ehrhardt,1,2 Vivian Chu,1,2 TeeCie Brown,1,3 Terrie L. Simmons,1,2 Brandon K. Swan,4 Jason Bannan,5 and James M. Robertson2*
      Federal Bureau of Investigation, Quantico, Virginia 22135,1 Counterterrorism and Forensic Science Research Unit, Federal Bureau of Investigation, Quantico, Virginia 22135,2 Department of Biochemistry and Molecular Biology, Oklahoma State University, Stillwater, Oklahoma 74078,3 Marine Science Program and Department of Earth Science, University of California at Santa Barbara, Santa Barbara, California 93106,4 Chemical and Biological Sciences Unit, FBI Laboratory Division, Quantico, Virginia 221355

      Received 8 October 2009/ Accepted 8 January 2010
      Excerpts:

      “Besides aiding in the identification of bacterial species, FAME profiling can potentially provide information on the methods used to grow microorganisms of forensic interest. Within the Bacillus group, the amino acid content or the type of complex additives used in the cultivation media can significantly affect the fatty acid composition of bacterial cultures. The relative proportions of branched fatty acids (iso-odd, iso-even, and anteiso), which are prevalent in Bacillus spp. (33, 36a), are heavily dependent on the ratio of amino acid precursors (leucine, valine, and isoleucine) and the corresponding -keto acids present in the growth media (12, 27, 28, 32). Accordingly, the complex additives and protein sources that supply these amino acid precursors in growth media also affect the fatty acid compositions of Bacillus cultures.
      ***

      Figure 3 shows the nMDS plot for spores grown on 10 sporulation media (Table 1, excluding CDSM). Spores grown on media with disparate chemical compositions exhibited well-defined clusters with high intergroup distances with respect to each other, suggesting significant multivariate dissimilarity. These media included LL, G, Sch, CAD, NSM, and BHI. Compositionally similar media, such as G and MG (Table 1), showed closely associated (but separated) clusters with each other. Noncompositional features also appeared to affect the FAME profiles of BcT spores. For example, SchAg samples (agar based) did not show a close association with Sch samples (broth based), exhibited high intragroup variation, and overlapped with other medium groups in the center of the nMDS plot (Fig. 3). Similarly, spores grown on CA and CAB showed higher intragroup variation and, in the case of CA, completely overlapped with BHI samples. The stress value reported in Fig. 3 (0.11) indicates that the nMDS plot is an accurate representation of intersample relationships (8).

      ***
      The main advantage of DFA for forensic studies is that it incorporates prior data structure into the analysis and allows the user to define sample groupings so that different levels of variation in the data set can be examined. In this way, differences among FAME profiles that may be due to experimental error among replicates or small variations in medium chemistry can be minimized and changes in FAME variables that are driven by distinguishing characteristics of the sporulation medium (e.g., complex additives, supplemental protein, or unusual compounds) can be identified. For example, Sch and SchAg have identical chemical compositions but differ in the physical state (broth and agar, respectively), which results in non-compositionally based variation in FAME profiles (Fig. 3 and Table 4). If all samples grown in either Sch or SchAg are defined in one group, then DFA will generate linear functions that minimize variation between the Sch and SchAg samples and maximize variation between these and other sporulation medium groups. The variables with the largest coefficients in these functions will then represent FAME biomarkers reflecting compositional differences, rather than the total dissimilarity between Sch/SchAg and other media.

      To identify FAME variables that are diagnostic for differences in protein content among sporulation media, discriminant functions were built to analyze eight composite medium groups reflecting different complex protein sources. Six of these groups were identical to the sample groups used for nMDS. However, spore samples for MG were grouped with G samples, since both represent media with yeast as the sole protein source (Table 1). Similarly, Sch and SchAg samples were combined into one group. The equations for the first two discriminant functions (or CVs), along with a 2D plot of the distribution of each sample in CV space, are shown in Fig. 4a.

      Samples belonging to the LL, G, and CAB groups are clearly differentiated from each other and from the remaining groups in the center of the plot (CA, CAD, NSM, BHI, and Sch). Separation between CAB and G occurs primarily along CV1, whereas the distances between the G and LL groups are found along CV2. The CAB and LL groups are separated along both CV1 and CV2. The coefficients for each CV function (on right of the plots) indicate that different sets of variables drive separation along each axis. CV1 is dominated by the relative proportions of 15:0 anteiso, 17:1 iso 10c, and 17:1 anteisoA, and CV2 is dominated by the relative proportions of 17:1 iso 10c and 17:1 iso 5c.

      Because little differentiation was observed among BHI, CA, CAD, NSM, and Sch samples (Fig. 4a), new discriminant functions were constructed using only these groups (Fig. 4b). Similar to the previous plot, two of the sample groups (CAD and Sch) can be easily distinguished from each other along CV1. However, the variables with the largest contribution to the differentiation among these groups are 14:0 iso, 16:0 iso, 17:1 iso 10c, and 17:1 iso 5c. The remaining groups (CA, BHI, and NSM) cannot be clearly discriminated from each other along CV1 or CV2 but are separated from CAD and Sch by both CV functions.

      When discriminant functions are built for the last three groups (BHI, CA, and NSM) (Fig. 4c), CV1 accounts for nearly all the variation among groups (90%) and clear separation in the CV plot is observed for every group. Unlike the previous functions, only branched-odd variables, 13:0 iso, 17:1 iso 10c, and 17:1 iso 5c, account for the variation along CV1.

      ***
      Oleic acid as a biomarker for media with blood supplements.
      The only fatty acid biomarker exclusive to any of the surveyed media was oleic acid (18:1 9c) from spores grown on Columbia agar supplemented with sheep blood. Oleic acid is predominantly associated with eukaryotic organisms (13) but can be introduced exogenously through blood supplements (45) or surfactants, such as Tween 80, during the preparation process (15). Also, oleic acid is a common feature in commercial FAME libraries that contain organisms grown on blood-supplemented substrates (G. Jackoway, MIDI Inc., personal communication). This, combined with the observation that oleic acid did not appear in significant quantities in BcT spores grown on the Columbia agar base (CA) (Table 3) but was present when spores were grown on other media containing blood products (tryptic soy agar with blood) (data not shown) suggests that this fatty acid is likely derived from the eukaryotic supplements in the CAB medium. Regardless of the origin, our results indicate that oleic acid may be a promising biomarker for Bacillus cultures grown on media that are supplemented with sheep blood products.

      Differentiation among medium groups using whole FAME profiles.
      Fatty acid analyses based on all FAME biomarkers showed that many of the 10 medium cultures in this study could be differentiated by their FAME profiles on the 2D nMDS plot (Fig. 3) and with pairwise R values (Table 4). The largest dissimilarities in FAME profiles were found among spores grown on media with distinctly disparate protein and nitrogen sources (yeast, meat peptone, yeast/casein peptone, brain heart infusion/gelatin digest, and beef extract/meat peptone for G, LL, CAD, BHI, and Sch, respectively). The dissimilarities in FAME profiles likely reflect the distinct differences in fatty acid precursors (amino acids and -keto acids) inherent in each of the above-mentioned medium formulations.

      Other media (BHI, CA, CAB, and SchAg) exhibited less distinct differences, as evidenced by cluster overlap (BHI-CA) or large intersample distances (CA, CAB, and SchAg). Overlapping sample groups could, in part, be indicative of the protein/amino acid composition of the sporulation medium. Both BHI and CA contain a variety of meat digest and beef infusion components (Table 1). Since different beef-derived supplements can have comparable ratios of leucine and isoleucine (35), the similarity in BHI and CA samples may reflect overlapping concentrations of these fatty acid precursors in each medium.

      Variation in FAME profiles was also observed between spores grown on media with identical substrate compositions but different physical states (Sch and SchAg). FAME differences between Bacillus cultures grown in agar and broth-based media with identical compositions have been observed previously (26, 41) and could be related to microenvironments that are created during sporulation on agar media. In Bacillus organisms, the synthesis of unsaturated fatty acids is mediated by desaturase enzymes that are oxygen dependent (14, 26). The relative proportions of unsaturated fatty acid markers, such as 16:17c, which is abundant in BcT FAME profiles (Table 3), is primarily affected by the concentration of the saturated fatty acid precursor (16:0) and oxygen availability (26). During growth on agar plates, the oxygen concentration may show spatial heterogeneities within BcT colonies that can affect the proportions of saturated and unsaturated fatty acid spore profiles compared to organisms grown in liquid media (26, 58). Similarly, metabolic substrates can show heterogeneities within agar colonies (39). This hypothesis would be consistent with shifts in the observed proportions of 16:1 7c (SumFeat2), 16:0 iso, and 15:0 iso for Sch and SchAg samples (Table 3). Consequently, statistical analyses (nMDS) based on all individual fatty acids would be prone to these variations, since each marker contributes independently to the calculated dissimilarity among samples. The observed discrepancies in FAME profiles between Sch and SchAg samples indicate that forensic discrimination of spores should incorporate different physical states of the medium.

      Similarities and differences in medium composition or physical state would not explain why the SchAg, CA, and CAB groups had larger dissimilarities among replicate samples. This FAME profile heterogeneity displayed within CA and CAB could reflect slight variation in the proportion of vegetative cells in these spore preparations (see Results). Alternatively, the period of incubation prior to spore harvesting varied more for CA, CAB, and SchAg than for broth-based media, which would affect the number of metabolic conversions and potentially the relative proportions of FAMEs. However, this idea does not hold for all agar groups, since BHI and LL did not show comparable levels of intragroup variation.

      Other medium pairs, mainly G-MG, showed distinct but closely related clusters on the nMDS plot and smaller R values for ANOSIM. Some dissimilarity between these two groups was expected, since the presence of different sugars in growth media has been found to affect the fatty acid profiles of Bacillus organisms (4, 11, 24, 52). Less dissimilarity between G and MG spore profiles suggests that small variations in supplemental sugar concentrations in the sporulation medium do not affect FAME profiles as significantly as other changes in the growth medium formulation.

      Ultimately, these results suggest that using raw calculations of dissimilarity generated from every variable constituting a FAME profile is insufficient to differentiate all spore groups. While the analysis does indicate that FAME differences are most pronounced when spores are prepared on media with different types of complex additives and nonoverlapping protein sources, it also shows that total profile dissimilarities can be affected by variations in other, nondefining attributes of the medium or by the intrinsic variability of certain spore-medium groups. To compensate for these effects, profiles need to be analyzed with a statistical technique that can minimize variation that is nonspecific to the protein/amino acid content of each medium and can extract signatures that are unique to its defining compositional characteristics.

      Differentiation of FAME profiles using DFA.
      The FAME biomarkers that responded most significantly to variation in the protein source were isolated by combining all spore samples that were grown in media with similar protein components and analyzing the resulting groups with DFA. A comparison of the clustering patterns in Fig. 3 and 4 indicates that non-compositionally based variation is minimized with DFA. For example, all Sch samples (composites of Sch and SchAg) showed a well-defined cluster with low intersample variation (Fig. 4a and b). Other groups exhibiting heterogeneities among replicates in nMDS (CA and CAB) displayed smaller intragroup variation in CV plots that were comparable to that of other spore groups (Fig. 4a and c). With non-compositionally based variation reduced, canonical variate functions and the corresponding high-magnitude FAME variables can be used to identify promising biomarkers for spore discrimination.

      Figure 4a shows that CV1, which was heavily influenced by the proportions of 15:0 anteiso and 17:1 anteisoA, clearly separated G and CAB samples from other media. However, CV1, and therefore these two FAME biomarkers, could not clearly distinguish G samples from LL, or any samples grown in BHI, NSM, Sch, CAD, or CA from each other. Different FAME biomarkers were responsible for differentiating each of these groups. Branched-even FAMEs 14:0 iso and 16:0 iso and branched-odd FAMEs 17:1 5c and 17:1 10c drove the separation for CAD and Sch groups (Fig. 4b). However, only branched-odd FAMEs were significant contributors to the CV functions differentiating NSM, BHI, and CA groups (Fig. 4c).

      These results suggest that FAME variation among all spore groups cannot be captured with a single set of equations but requires multiple, successive CV functions to discriminate among all spore groups. Also, the varying contributions of individual FAMEs to CV-based differentiation indicate that the same set of FAME variables cannot differentiate all spore groups simultaneously. For example, 15:0 anteiso and 17:1 anteisoA distinguished G-medium samples from other groups but poorly discriminated Sch and CAD from other samples. Conceptually, this is reasonable, since medium formulations may show variation across different sets of amino acid precursors, and spores grown on these media should vary across different sets of FAME variables.

      Due to these observations, DFA-based discrimination of spores grown on different media may necessitate a hierarchically structured analysis similar to that portrayed in Fig. 4. In such a system, FAME profiles would be subjected to a cascading system of discriminant functions that model variation across separate subsets of reference groups (23). Taking Fig. 4 as an example, the FAME profile of an unknown microbial sample would first be run through an initial set of discriminant functions (Fig. 4a) and classified as belonging to either G, CAB, LL, or the unresolved group composed of BHI, CA, Sch, NSM, and CAD. If the sample was most closely related to the unresolved group, the FAME profile would be analyzed with the second set of discriminant functions (Fig. 4b), classifying it as either Sch, BHI, or the unresolved group composed of BHI, CA, and NSM. If the sample again was most closely related to the unresolved group, subsequent discriminant functions (Fig. 4c) would be used until a singular identification was acquired. Tiered classification systems with DFA have been used successfully in other forensic systems (23, 46) and could be applied to microbial samples provided that the discriminant functions are built from a comprehensive reference database (in this case, a library of FAME profiles from spores grown in various media).

      Conclusions and future work.
      Overall, the results indicate that variations in BcT FAME profiles can be used to discriminate among spores grown on different media. While individual biomarkers, such as oleic acid, may be diagnostic for certain components of the growth medium, the majority of variation across FAME profiles is driven by differences in the protein or amino acid sources in each sporulation medium. Other characteristics of the medium, such as the physical state or the concentration of glucose, do affect FAME profiles to an extent. Nevertheless, these profile variations can be reduced with DFA so that the FAME signatures that are specific for formulations with unique combinations of complex additives or supplemental protein sources can be detected.

      Although this is an important first step for determining whether FAME profiling can be a forensic tool, much work remains before the observed differences among cultures grown on different media can be translated into forensically relevant biosignatures. First, the hypothesis that FAME variation is diagnostic for the combination of complex additives and protein sources that are present in each medium formulation should be explicitly tested by expanding a FAME data set to include formulations that vary in the concentrations of identical protein sources. Second, the effects that environmental factors, such as growth temperature, pH, or dissolved oxygen, have on FAME profiles should be compared to the compositionally based variation reported here. Third, different subsets of FAME variables should be identified with alternative statistical techniques, such as stepwise DFA (48) or Bayesian variable selection (2), and compared to the discriminatory power of the FAME subset used in this study.

      Most significantly, multivariate strategies that allow sample profiles to be matched statistically to FAME databases are needed. The discriminant function analyses shown here are descriptive in nature (21) and are not intended to be robust classification schemes. A separate statistical procedure termed “predictive DFA” can be used for this purpose and is a promising strategy for classification of unknown samples (48). However, this technique still needs to be tested on a microbial data set. Another possibility is “Bayesian network analysis” (23), which would allow FAME databases to be combined with other orthogonal data sets (isotope, SIMS, etc.) to characterize a microbial sample of unknown origin. Future strategies may need to incorporate a combination of the above-mentioned approaches in order to successfully reduce the intrinsic complexity of FAME profiles and to help this technique become a viable tool in forensic microbiology.

      ACKNOWLEDGMENTS
      We gratefully acknowledge the laboratory contributions of Matt Ducote and Mark Reimers. We also thank Keith Monson, Robert Koons, Bruce Budowle, Robert Bull, Ulrich Melcher, and Lilliana Moreno for their discussions and informal reviews of the manuscript.
      This research was supported in part by the Visiting Scientist Program, an educational opportunity administered by the Oak Ridge Institute for Science and Education.

      The names of commercial manufacturers are provided for information only and do not imply endorsement by the Federal Bureau of Investigation (FBI) or the U.S. Government. The conclusions are those of the authors and should not be taken as necessarily representing the views, either expressed or implied, of the U.S. Government.

      This is publication no. 09-08 of the Laboratory Division of the FBI.

      FOOTNOTES
      * Corresponding author. Mailing address: 2501 Investigation Parkway, Counterterrorism and Forensic Science Research Unit, Quantico, VA 22135. Phone: (703) 632-4555. Fax: (703) 632-4500. E-mail: james.m.robertson@ic.fbi.gov

      Published ahead of print on 22 January 2010.

      REFERENCES Top
      ABSTRACT
      INTRODUCTION
      MATERIALS AND METHODS
      RESULTS
      DISCUSSION
      REFERENCES

      1
      Aronson, A. I., N. Angelo, and S. C. Holt. 1971. Regulation of extracellular protease production in Bacillus cereus T: characterization of mutants producing altered amounts of protease. J. Bacteriol. 106:1016-1025.[Abstract/Free Full Text]2
      Banowetz, G. M., G. W. Whittaker, K. P. Dierksen, M. D. Azevedo, A. C. Kennedy, S. M. Griffith, and J. J. Steiner. 2006. Fatty acid methyl ester analysis to identify sources of soil in surface water. J. Environ. Qual. 35:133-140.[Abstract/Free Full Text]3
      Beecher, D. J. 2006. Forensic application of microbiological culture analysis to identify mail intentionally contaminated with Bacillus anthracis spores. Appl. Environ. Microbiol. 72:5304-5310.[Abstract/Free Full Text]4
      Bezbaruah, R. L., K. R. Pillai, B. K. Gogoi, and J. N. Baruah. 1988. Effect of growth temperature and media composition on the fatty acid composition of Bacillus stearothermophilus AN 002. Antonie Van Leeuwenhoek 54:37-45.[CrossRef][Medline]5
      Reference deleted.6
      Carrera, M., R. O. Zandomeni, J. Fitzgibbon, and J.-L. Sagripanti. 2007. Differences between the spore sizes of Bacillus anthracis and other Bacillus species. J. Appl. Microbiol. 102:303-312.[Medline]7
      Church, B. D., H. Halvorson, and H. O. Halvorson. 1954. Studies on spore germination: its independence from alanine racemase activity. J. Bacteriol. 68:393-399.[Free Full Text]8
      Clarke, K. R. 1993. Non-parametric multivariate analyses of changes in community structure. Aust. J. Ecol. 18:117-143.[CrossRef]9
      Clarke, K. R., and R. M. Warwick. 1994. Change in marine communities: an approach to statistical analysis and interpretation. Natural Environment Research Council, Plymouth, United Kingdom.10
      Cliff, J. B., K. H. Jarman, N. B. Valentine, S. L. Golledge, D. J. Gaspar, D. S. Wunschel, and K. L. Wahl. 2005. Differentiation of spores of Bacillus subtilis grown in different media by elemental characterization using time-of-flight secondary ion mass spectrometry. Appl. Environ. Microbiol. 71:6524-6530.[Abstract/Free Full Text]11
      Daron, H. H. 1970. Fatty acid composition of lipid extracts of a thermophilic Bacillus species. J. Bacteriol. 101:145-151.[Abstract/Free Full Text]12
      Daron, H. H. 1973. Nutritional alteration of the fatty acid composition of a thermophilic Bacillus species. J. Bacteriol. 116:1096-1099.[Abstract/Free Full Text]13
      Dye, E. S., and F. A. Kapral. 1981. Characterization of a bactericidal lipid developing within staphylococcal abscesses. Infect. Immun. 32:98-104.[Abstract/Free Full Text]14
      Fulco, A. J. 1983. Fatty acid metabolism in bacteria. Prog. Lipid Res. 22:133-160.[CrossRef][Medline]15
      Guerzoni, M. E., R. Lanciotti, and P. S. Cocconelli. 2001. Alteration in cellular fatty acid composition as a response to salt, acid, oxidative and thermal stresses in Lactobacillus helveticus. Microbiology 147:2255-2264.[Abstract/Free Full Text]16
      Haack, S. K., H. Garchow, D. A. Odelson, L. J. Forney, and M. J. Klug. 1994. Accuracy, reproducibility, and interpretation of fatty acid methyl ester profiles of model bacterial communities. Appl. Environ. Microbiol. 60:2483-2493.[Abstract/Free Full Text]17
      Hageman, J. H., G. W. Shankweiler, P. R. Wall, K. Franich, G. W. McCowan, S. M. Cauble, J. Grajeda, and C. Quinones. 1984. Single, chemically defined sporulation medium for Bacillus subtilis: growth, sporulation, and extracellular protease production. J. Bacteriol. 160:438-441.[Abstract/Free Full Text]18
      Hashimoto, T., S. H. Black, and P. Gerhardt. 1960. Development of fine structure, thermostability, and dipicolinate during sporogenesis in a bacillus. Can. J. Microbiol. 6:203.[Medline]19
      Helgason, E., O. A. Okstad, D. A. Caugant, H. A. Johansen, A. Fouet, M. Mock, I. Hegna, and A. B. Kolsto. 2000. Bacillus anthracis, Bacillus cereus, and Bacillus thuringiensis—one species on the basis of genetic evidence. Appl. Environ. Microbiol. 66:2627-2630.[Abstract/Free Full Text]20
      Hoffmaster, A., C. Fitzgerald, E. Ribot, and L. Mayer. 2002. Molecular subtyping of Bacillus anthracis and the 2001 bioterrorism-associated anthrax outbreak, United States. Emerg. Infect. Dis. 8:1111-1116.[Medline]21
      Huberty, C. J. 1994. Applied discriminant analysis. John Wiley and Sons, Inc., New York, NY.22
      Jarman, K. H., H. W. Kreuzer-Martin, D. S. Wunschel, N. B. Valentine, J. B. Cliff, C. E. Petersen, H. A. Colburn, and K. L. Wahl. 2008. Bayesian-integrated microbial forensics. Appl. Environ. Microbiol. 74:3573-3582.[Abstract/Free Full Text]23
      Johnson, D. R., P. O’Higgins, W. J. Moore, and T. J. McAndrew. 1989. Determination of race and sex of the human skull by discriminant functions analysis of linear and angular dimensions. Forensic Sci. Int. 41:41-53.[CrossRef][Medline]24
      Kaneda, T. 1971. Factors affecting the relative ratio of fatty acids in Bacillus cereus. Can. J. Microbiol. 17:269-275.[CrossRef][Medline]25
      Kaneda, T. 1967. Fatty acids in the genus Bacillus I. Iso- and anteiso-fatty acids as characteristic constituents of lipids in 10 species. J. Bacteriol. 93:894-903.[Abstract/Free Full Text]26
      Kaneda, T. 1968. Fatty acids in the genus Bacillus II. Similarity in the fatty acid compositions of Bacillus thuringiensis, Bacillus anthracis, and Bacillus cereus. J. Bacteriol. 95:2210-2216.[Abstract/Free Full Text]27
      Kaneda, T. 1977. Fatty acids of the genus Bacillus: an example of branched-chain preference. Bacteriol. Rev. 41:391-418.[Free Full Text]28
      Kaneda, T. 1991. Iso- and anteiso-fatty acids in bacteria: biosynthesis, function, and taxonomic significance. Microbiol. Rev. 55:288-302.[Abstract/Free Full Text]29
      Kim, W. Y., T. W. Song, M. O. Song, J. Y. Nam, C. M. Park, K. J. Kim, S. I. Chung, and C. S. Chol. 2001. Analysis of cellular fatty acid methyl esters (FAMEs) for the identification of Bacillus anthracis. J. Korean Soc. Microbiol. 35:31-40.30
      Kreuzer-Martin, H. W., L. A. Chesson, M. J. Lott, J. Dorigan, and J. R. Ehleringer. 2004. Stable isotope ratios as a tool in microbial forensics, 2. Isotopic variations among different growth media as a tool for sourcing origins of bacterial cells or spores. J. Forensic Sci. 49:961-967.[Medline]31
      Kreuzer-Martin, H. W., M. J. Lott, J. Dorigan, and J. R. Ehleringer. 2003. Microbe forensics: oxygen and hydrogen stable isotope ratios in Bacillus subtilis cells and spores. Proc. Natl. Acad. Sci. U. S. A. 100:815-819.[Abstract/Free Full Text]32
      Lawrence, D., S. Heitefuss, and H. S. Seifert. 1991. Differentiation of Bacillus anthracis from Bacillus cereus by gas chromatographic whole-cell fatty acid analysis. J. Clin. Microbiol. 29:1508-1512.[Abstract/Free Full Text]33
      Lechevalier, M. P. 1977. Lipids in bacterial taxonomy. Crit. Rev. Microbiol. 5:109-210.[CrossRef]34
      Leonard, R. B., J. Mayer, M. Sasser, M. L. Woods, B. R. Mooney, B. G. Brinton, P. L. Newcomb-Gayman, and K. C. Carroll. 1995. Comparison of MIDI Sherlock system and pulsed-field gel electrophoresis in characterizing strains of methicillin-resistant Staphylococcus aureus from a recent hospital outbreak. J. Clin. Microbiol. 33:2723-2727.[Abstract/Free Full Text]35
      Loginova, L. I., V. P. Manuilova, and V. P. Tolstikov. 1974. Content of free amino acids in peptone and the dynamics of their consumption in the microbiological synthesis of dextran. Pharm. Chem. Factory 8:49-51.36
      Manly, B. F. J. 2005. Multivariate statistical methods, 3rd ed. Chapman & Hall, Boca Raton, FL.36a
      O’Leary, W. M., and S. G. Wilkinson. 1988. Gram-positive bacteria, p. 155-159. In C. Ratledge and S. G. Wilkinson (ed.), Microbial lipids, vol. 1. Academic Press, New York, NY.37
      Peak, K. K., K. E. Duncan, W. Veguilla, V. A. Luna, D. S. King, L. Heller, L. Heberlein-Larson, F. Reeves, A. C. Cannons, P. Amuso, and J. Cattani. 2007. Bacillus acidiceler sp. nov., isolated from a forensic specimen, containing Bacillus anthracis pX02 genes. Int. J. Syst. Evol. Microbiol. 57:2031-2036.[Abstract/Free Full Text]38
      Ratledge, C., and S. G. Wilkinson. 1988. Microbial lipids, vol. 1. Academic Press Inc., New York, NY.39
      Rieck, V. T., S. A. Palumbo, and L. D. Witter. 1973. Glucose availability and the growth rate of colonies of Pseudomonas fluorescens. J. Gen. Microbiol. 74:1-8.[Abstract/Free Full Text]40
      Robertson, J., C. J. Ehrhardt, and J. Bannan. Lipids in microbial forensics. In J. Cliff (ed.), Microbial forensics, in press. Humana Press, Totowa, NJ.41
      Rose, R., B. Setlow, A. Monroe, M. Mallozzi, A. Driks, and P. Setlow. 2007. Comparison of the properties of Bacillus subtilis spores made in liquid or on agar plates. J. Appl. Microbiol. 103:691-699.[CrossRef][Medline]42
      Sasser, M. 1990. Identification of bacteria by gas chromatography of cellular fatty acids. MIDI technical note. MIDI, Newark, DE.43
      Scandella, C. J., and A. Kornberg. 1969. Biochemical studies of bacterial sporulation and germination XV. Fatty acids in growth, sporulation, and germination of Bacillus megaterium. J. Bacteriol. 98:82-86.[Abstract/Free Full Text]44
      Schaeffer, P., J. Millet, and J. P. Aubert. 1965. Catabolic repression of bacterial sporulation. Proc. Natl. Acad. Sci. U. S. A. 54:704-711.[Free Full Text]45
      Scherer, C., K.-D. Muller, P.-M. Rath, and R. A. M. Ansorg. 2003. Influence of culture conditions on the fatty acid profiles of laboratory-adapted and freshly isolated strains of Helicobacter pylori. J. Clin. Microbiol. 41:1114-1117.[Abstract/Free Full Text]46
      Snow, C. C., S. Hartman, E. Giles, and F. A. Young. 1979. Sex and race determination of crania by calipers and computer: a test of the Giles and Elliot discriminant functions in 52 forensic science cases. J. Forensic Sci. 24:448-460.[Medline]47
      Song, Y., R. Yang, Z. Guo, M. Zhang, X. Wang, and F. Zhou. 2000. Distinctness of spore and vegetative cellular fatty acid profiles of some aerobic endospore-forming bacilli. J. Microbiol. Methods 39:225-241.[CrossRef][Medline]48
      Tabachnick, B. G., and L. S. Fidell. 2001. Using multivariate statistics. Allyn & Bacon, Needham Heights, MA.49
      Teska, J. D., S. R. Coyne, J. W. Ezzell, C. M. Allan, and S. L. Redus. 2003. Identification of Bacillus anthracis using gas chromatographic analysis of cellular fatty acids and a commercially available database, p. 1-5. Agilent Technologies Inc., Santa Clara, CA.50
      Vandamme, P., B. Pot, M. Gillis, P. DeVos, K. Kersters, and J. Swings. 1996. Polyphasic taxonomy, a consensus approach to bacterial systematics. Microbiol. Rev. 60:407.[Abstract/Free Full Text]51
      Von Wintzingerode, F., F. A. Rainey, R. M. Kroppenstedt, and E. Stackebrandt. 1997. Identification of environmental strains of Bacillus mycoides by fatty acid analysis and species-specific rDNA oligonucleotide probe. FEMS Microbiol. Ecol. 24:201-209.52
      Weerkamp, A., and W. Heinen. 1972. The effect of nutrients and precursors on the fatty acid composition of two thermophilic bacteria. Arch. Microbiol. 81:350-360.53
      Welch, D. F. 1991. Applications of cellular fatty-acid analysis. Clin. Microbiol. Rev. 4:422-438.[Abstract/Free Full Text]54
      Weyent, R. S., C. W. Moss, R. E. Weaver, D. G. Hollis, J. G. Jordan, E. C. Cook, and M. I. Daneshvar. 1996. Bacterial identification by cellular fatty acid analysis, p. 565-721, Identification of unusual Gram-negative aerobic and facultatively anaerobic bacteria, 2nd ed. Williams & Wilkins, Baltimore, MD.55
      White, D. C., C. A. Lytle, M. G. Ying-Dong, Y. M. Piceno, M. H. Wimpee, A. D. Peacock, and C. A. Smith. 2002. Flash detection/identification of pathogens, bacterial spores and bioterrorism agent biomarkers from clinical and environmental matrices. J. Microbiol. Methods 48:139-147.[CrossRef][Medline]56
      Whiteaker, J., and C. Fenselau. 2004. Quantitative determination of heme for forensic characterization of Bacillus spores using matrix assisted laser desorption/ionization time-of-flight mass spectrometry. Anal. Chem. 76:2836-2841.[Medline]57
      Whittaker, P., F. S. Fry, S. K. Curtis, S. F. Al-Khaldi, M. M. Mossoba, M. P. Yurawecz, and V. C. Dunkel. 2005. Use of fatty acid profiles to identify food-borne bacterial pathogens and aerobic endospore-forming bacilli. J. Agric. Food Chem. 53:3735-3742.[CrossRef][Medline]58
      Wimpenny, J. W. T., and J. P. Coombs. 1983. Penetration of oxygen into bacterial colonies. J. Gen. Microbiol. 129:1239-1242.[Abstract/Free Full Text]59
      Wunschel, D. S., H. A. Colburn, A. Fox, K. F. Fox, W. M. Harley, J. H. Wahl, and K. L. Wahl. 2008. Detection of agar, by analysis of sugar markers, associated with Bacillus anthracis spores, after culture. J. Microbiol. Methods 74:57-63.[CrossRef][Medline]

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

 
%d bloggers like this: