Chemical elements in mushrooms: their potential taxonomic significance

ORIGINAL ARTICLE

Chemical elements in mushrooms: their potentialtaxonomic significance

Orlando Petrini & Luigi Cocchi & Luciano Vescovi &Liliane Petrini

Received: 3 November 2008 /Revised: 8 February 2009 /Accepted: 17 February 2009# German Mycological Society and Springer-Verlag 2009

Abstract One inherent problem in taxonomy is the choiceof an internal or external reference. Phylogenetic studiesroutinely use outgroups, but classical taxonomy studiesoften lack internal or external controls. We suggest theestablishment of internal references when dealing with largeamounts of data that can be summarised by descriptivestatistics. This study introduces the use of group centroids(i.e., “reference fungi”) in taxonomy and describes thepotential utility of chemical elements and methods ofinorganic analytical chemistry in fungal taxonomy, usingmacromycete fruiting bodies as an example. Macromycetesare known to accumulate high levels of various chemicalelements, in particular heavy metals. Their concentration isassumed to be species-specific, but substrate compositionmay also influence their presence in the mycelium and

fruiting bodies. We have analysed the distribution of severalchemical elements in a large sample of approximately 9,000ascomycetous and basidiomycetous fruiting bodies, inves-tigated in a study carried out during the last 20 years usingunivariate and multivariate methods. An internal controlthat we have called the “reference fungus” has been definedas the group average in univariate and group centroid inmultivariate analyses. This has been useful to detect majordeviations of selected samples from the mean values of thedataset. This methodology may be applied to any data,including morphological or ecological characters that canbe summarised by descriptive statistics. The internalcontrols must be defined on a case-by-case basis.

Keywords Taxonomy . Reference fungus .

Chemical elements . Ascomycetes . Basidiomycetes

Introduction

Fungal taxonomy is at a turning point: mycologists areslowly moving from the classification of fungi using onlyone set of characters to polyphasic taxonomy, a moreintegrated approach that tries to integrate morphological,physiological, molecular biology and ecological data toreach a more accurate and reliable classification. Mycolog-ical work has traditionally relied upon morphologicalcharacters to identify and characterise taxa (Ju and Rogers1999; Miller 1961; Petrini LE 1992; 2003; Schroers 2001),and physiology has shown its utility in characterisingfungal organisms. Cell wall composition has led to theseparation of higher fungal taxa (Barr 1992). The identifi-cation of yeasts still relies heavily on physiological tests(Boekhout 1991; de Hoog 1999; de Hoog and Hermanides-Nijhof 1977). Substrate utilisation studies have been

Mycol ProgressDOI 10.1007/s11557-009-0589-1

O. PetriniCantonal Institute of Microbiology,Bellinzona, Switzerland

L. Cocchi : L. VescoviMycological and Naturalistic Group “R. Franchi” (A.M.B.),Reggio Emilia, Italy

L. CocchiNational Scientific Committee of AssociazioneMicologica Bresadola,via A. Volta, 46,Trento 38100, Italy

L. VescoviEnìa S.p.A.,via Nubi di Magellano 30,Reggio Emilia, Italy

L. Petrini (*)Via al Perato 15c,Breganzona, Switzerlande-mail: [email protected]

employed to identify basidiomycetes and characterise otherfungi in culture (Carroll and Petrini 1983; Leuchtmann etal. 1992; Nobles 1965; Petrini LE et al. 1991). Biochemicalmethods have been introduced in mycology to furthercharacterise fungal genera and species (Petrini O. et al.1989; Rodrigues et al. 1995; Stadler and Wollweber 2004;Stadler et al. 2001a, b, c, 2004); molecular biology is nowroutinely used in mycology and has helped to answer, atleast partly, hitherto unsolved taxonomic problems (deHoog 1999; Hsieh et al. 2005; Triebel et al. 2005;Untereiner et al. 1995). The combined use of different setsof data provides a realistic picture of the importance ofphenotype-based data as compared to molecular data alone(Varga et al. 2007).

The significance of chemical elements as markers forfungal taxonomy, on the other hand, is still unclear, yetenough information is available to justify investigations inthis field.

Mushrooms are a suitable model to study the role ofchemical elements in taxonomy because they are known toaccumulate high levels of various elements, in particularheavy metals (Allen and Steinnes 1978; Cocchi andVescovi 1997; Cocchi et al. 2006; Dojmi Di Delupis andDojmi Di Delupis 1996; Garcıá 1998; Kalac and Svoboda2000; Stegnar et al. 1973). We have previously reportedthat the presence and amounts of some heavy metals couldbe species-specific and of taxonomic use (Cocchi et al.2006), but substrate composition can also influence theiraccumulation in the mycelium and fruiting bodies (Cocchiand Vescovi 1997; Kalac and Svoboda 2000; Stijve et al.2004). However, so far, no specific studies have addressedthe potential use of chemical elements in fungal taxonomy.

One inherent problem in taxonomy is the choice of areference to be used as an internal or external control.Phylogenetic studies have solved it with the introduction ofoutgroups (Maddison et al. 1984), but internal controls aremostly lacking in classical taxonomy studies. However,when large amounts of data can be summarised bydescriptive statistics, the use of group centroids to establishinternal references may be a useful approach to establishinternal and external controls, which, in mycology, wepropose to call “reference fungus”. This can be defined as ahypothetical mushroom described by the average of eachparameter studied (the group average in univariate andgroup centroid in multivariate analyses—in the followingreferred, for simplicity, as centroid or “reference”) andcomparable to the “reference man” established by theInternational Commission on Radiological Protection(ICRP) (Snyder et al. 1975) or the “reference plant”described by Markert (1992a). Clearly, the centroid isheavily influenced by the size and structure of the sample.In medicine this has been highlighted, for example, by thework carried out on variations of the “reference man”

(Akhter et al. 2001; Ellis 1990; Jain et al. 1995; Lindskoug1992; Tanaka et al. 1989, 1998). It is obvious, therefore,that different “reference fungi” may need to be used fordifferent analyses and this could lead, within the samestudy, to the definition of several references that will bederived from sub-samples of the main sample.

This study aims at introducing the use of group centroids(i.e., “reference fungi”) in taxonomy using selected chem-ical elements of macromycete fruiting bodies as an exampleof the potential impact of this method in fungal taxonomy.

Material and methods

Material examined

We have analysed the distribution of several chemicalelements in a large sample of approximately 9,000ascomycetous and basidiomycetous fruiting bodies, inves-tigated during a study carried out during the last 20 years(Cocchi and Vescovi 1997; Cocchi et al. 2006).

Most samples were collected in Italy and particularly inthe region of Reggio Emilia, but fruiting bodies gathered inother geographic origins were also included. Samples werecollected directly by two of us (L.C. and L.V.) or bycorresponding members of the Mycological Society Bresa-dola. Chemical analyses were carried out in the chemicallaboratory of the Enìa S.p.A. in Reggio Emilia.

The choice of fungal taxa to be studied was based onpurely pragmatic criteria. An exploratory analysis showedthat Amanitales had an overall chlorine content thatconsistently distinguished them from all other mushroomorders. Selenium and mercury were most abundant in theBoletales, in particular taxa in the Boletus edulis group;additionally, phylogenetic analyses have been carried outwithin the Boletales, thus providing the opportunity ofverifying the concordance of grouping performed byphylogenetic and chemical analysis (Vizzini et al. 2007).Finally, we included the Russulales, with basically only twolarge genera, both well represented in our database. Othertaxa were included to provide additional examples of theconsistency of the presence or absence of selected elementswithin a given species or genus. The taxa studied are listedin Table 1. The nomenclature used follows the taxonomyby Courtecuisse and Duhem (1994) and Papetti et al.(1999).

Chemical methods

Chemical analyses were carried out as described by Cocchiet al. (2006). Briefly, ascomycetous and basidiomycetousfruiting bodies were first cleaned manually from soil andsubstrate and exsiccated at 40–60°C during at least 24 h.

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Samples (0.5–0.7 g) were put in Teflon containers, mixedwith 10 ml HNO3 and incubated for 30 min in a microwaveoven (Perkin Elmer Multiwave®) at approximately 180°Cat 30 bar. The material obtained from the mineralisationwas diluted with deionised H2O to yield a sample of 50 ml.The quantitative determination of the chemical elementswas carried out using an ICP-OES Perkin Elemer Optima3000 XL spectrophotometer, with the exception of Hg thatwas determined by atomic absorption spectroscopy using acold-vapour Perkin Elmer FIMS 100 (Markert 1992b;Tsaler and Zaprianov 1985).

Statistical analysis

For each fungal species descriptive statistics [minimum,mean, median, maximum, and 95% confidence intervals(CI)] were computed for the concentrations of the selectedchemical elements (Ag, Al, As, B, Ba, Ca, Cd, Cl, Co, Cr,Cs, Cu, Fe, Hg, K, Mg, Mn, Na, Ni, P, Pb, Rb, S, Se, Sr, Ti,Zn, Zr, V), and the means and corresponding 95% CI wereused to display graphically differences among taxa.

A multivariate ordination analysis was carried out on thestandardised median values (mg/kg dry weight) of the

Order Genera included(n)

Species examined Total number ofrecords

Agaricales 10 – 911

Amanitales 2 546

Boletales 20 Boletus aereus Bull. 1,594B. aestivalis (Paulet) Fr.

B. calopus Pers.

B. edulis Bull.

B. edulis group

B. luridus Schaeff.

B. pinophilus Pilát & Dermek

B. pulverulentus Opat.

B. rhodopurpureus Smotl.

Leccinum duriusculum (Schulzer) Singer

Suillus granulatus (L.) Roussel

S. luteus (L.) Roussel

Xerocomus rubellus (Krombh.) Quél.

X. subtomentosus (L.) Quél.

Cantharellales 5 – 188

Clavariales 6 – 231

Cortinariales 22 – 1,394

Entolomatales 4 – 176

Lycoperdales 8 Calvatia utriformis (Bull.) Jaap 189Langermannia gigantea (Batsch) Rostk.

Pezizales 21 – 307

Polyporales 34 – 268

Reference 220 – 8,999

Russulales 2 Lactarius chrysorrheus Fr. 979L. deterrimus Gröger

L. piperatus (L.) Pers.

L. salmonicolor R. Heim & Leclair

Russula chloroides (Krombh.) Bres.

R. cyanoxantha (Schaeff.) Fr.

R. decipiens (Singer) Kühner & Romagn.

R. foetens (Pers.) Pers.

R. lepida Fr.

R. ochrospora (Nicolaj ex Quadr. & W.Rossi) Quadr.

R. vesca Fr.

Tricholomatales 40 – 1,793

Table 1 Fungal orders and spe-cies studied and number ofrecords within each order

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elements using monotonic multidimensional scaling(MDS), a data reduction procedure that can be used on asimilarity or dissimilarity matrix. Due to the skeweddistribution of the values within each dataset, we decidedagainst the use of mean values for the MDS procedure,because medians would better represent the distributionthan the mean values. In selected examples, for whichenough cases were available, classification was thenperformed using canonical discriminant analysis. As weconsider this an exploratory study, no confirmatory testswere carried out. All statistical analyses were performedusing SPSS 14 (SPSS, Chicago, IL, USA) on a PC runningWindows XP.

Results and discussion

Univariate analyses

Mushrooms have been described as potential bioindicators ofenvironmental pollution because of their ability to enrichheavy metals (Bargagli 1998; Cocchi and Vescovi 1997;Kalac and Svoboda 2000). The accumulation of certain ionsmay be mediated by the chemical composition of specificpigments located in the caps of the basidiocarps of someboletoid Basidiomycetes (Aumann et al. 1989). Ions of otherelements (e.g. Cl, Cu, Fe, Mg, Mn) are naturally present inliving organisms as components of enzymatic complexes.Other physiological factors, including the presence of side-rophores in the sporocarps of macromycetes, may alsocontribute to their accumulation. To use chemical elementsas taxonomic markers it is crucial to show that the amount of agiven element in a fungal taxon is independent of thegeographic origin of the sample, its habitat or other ecologicaland physiological factors that may influence uptake ofchemical compounds from the soil or the atmosphere.

Figure 1 displays the amounts of Se present in samplesof Boletus spp. (particularly in B. pinophilus) from differentgeographic origins, Zr in Amanita spp. (particularly in A.muscaria) in dependence of the habitat in which thesamples were collected, and Hg in Agaricus spp. (particu-larly in A. alberti) collected at different elevations.Although the ranges covered by the 95% CI are in mostcases quite large, also because of the comparatively smallsize of the samples, the differences among samples are notstatistically significant, thus indicating that these elementsare accumulated independently of the origin of the samplesexamined. Additional analysis of the complete dataset, bywhich we compared samples of the same species collectedin polluted versus unpolluted areas (data not shown)confirms these results and does not indicate any relevantbioindicator role of the mushrooms studies, as alreadyreported elsewhere (Cocchi et al. 2006).

Some chemical elements are present in selected fungaltaxa in amounts that set them apart from other fungi.Calvatia utriformis is characterised by an extremely highcontent of Pb, and this taxon and its closely relatedLangermannia gigantea both contain amounts of phospho-rous that separate them from other taxa and the centroids ofother selected groups (Fig. 2). While these results are ofinterest to highlight the usefulness of the statistical methodsdescribed, nevertheless the lack of data on closest relatives

Fig. 1 Content of selected chemical elements Selenium, Zirconium,Mercurium (Se, Zr, Hg) in mushroom samples collected from differentgeographic origins, habitats and elevations. a.s.l. Above sea level, CIconfidence interval

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of these two taxa somewhat limits the taxonomicsignificance of the results. The presence of very highquantities of chlorine in Amanita spp. (Fig. 3) allows theseparation of the Amanitales from all other orders investi-gated. Within the taxa studied, A. phalloides can be easilydistinguished from all other species, which in turn can bedivided into two groups (A. caesarea and A. muscaria vs A.citrina and A. rubescens). A similar situation can be seen inthe Boletales (Fig. 4). Boletus spp. in the Boletus edulisgroup tend to accumulate large amounts of Se that are notpresent in other species of the same or other orders. Onlysome Polyporales may contain large amounts of Se that,however, do not reach the levels recorded in the Boletusedulis group.

These results suggest that selected chemical elementscan be used to distinguish taxonomic entities. Theseparation may be set already at ordinal level, as is thecase for chlorine in the Amanitales, or at group or section,as shown for Se in the B. edulis group, or even at specieslevel (C. utriformis).

Multivariate analyses

Multidimensional scaling (MDS) has shown grouping oftaxa that are characterised by the presence of similaramounts of selected chemical elements. For all analyses,the data fitted the models quite well, with the stress ofthe final configurations in the range 0.005–0.03. If theordination is carried out at the ordinal level (Fig. 5), theAmanitales and the Lycoperdales are distinguished fromall other orders mostly because of the presence of highamounts of Cl, Zr, and V in the Amanitales, and of P andPb in the Lycoperdales. For the Lycoperdales, however,the limitations of the sample discussed in the precedingsection apply also here.

The Cantharellales also seem to be distinct from all othergroups: in this case, the distinction is based on severalvariables rather than on marked differences in one element,although the representatives of this order tend to have ratherhigh amounts of boron as compared to other samples. In thegraph, the position of the Pezizales, the only ascomycetous

Fig. 2 Phosphorus (P) and lead(Pb) content of Calvatia utri-formis and Langermanniagigantea compared to that ofother fungal species and thereferences. A Amanita, BBoletus, C Calvatia, LLangermannia, R Russula, CIconfidence interval

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group studied here, is closer to the remaining basidiomy-cetous orders than Amanitales or Lycoperdales. This maydepend on several factors, the most important of whichbeing the rather small sample size and the choice ofchemical elements that is somewhat biased towards thelarge basidomycetous dataset.

Taxa belonging to the B. edulis group, in particular in B.pinophilus, contain rather high amounts of Se (Fig. 4). Inthe MDS model, the first dimension separates the species inthe B. edulis group from the other taxa examined (Fig. 6).Within this group, the second MDS dimension defines twosubgroups, B. aereus and B. aestivalis on the one hand andon the other B. edulis s.s., B. pinophilus and other, notunequivocally identifiable taxa in the B. edulis group.Identification performed using canonical discriminant analysishas further confirmed the separation of these five entities(Table 2). The groupings are quite consistent, with B. edulisand B. pinophilus achieving an excellent discrimination(>70% of correct identification). The relatively poordiscrimination of the other two taxa (26% for B. aereus and21% for B. aestivalis) is most likely linked to the presence ofsamples belonging to these species in the sub-sample of B.

edulis group, to which 41% of the B. aereus and 47% of theB. aestivalis samples were assigned.

Conclusions

Our study has shown that chemical elements may be of usein the taxonomic classification of fungal taxa. In somecases, one element may be enough to unequivocallycharacterise a higher rank (order, genus) or specific taxon,as is the case with chlorine for the Amanitales and, withinthis order, for A. phalloides, or with selenium for species inthe B. edulis group. Some of our results indicate (at least inthose taxa for which a significant number of samples havebeen studied) that the distribution of certain chemicalelements can be used as taxonomic markers for selectedspecies, genera, and higher taxa. The inclusion of centroidshelps to highlight the correlation between the presence ofgiven element and the taxonomic position of the samplestudied.

For this kind of analysis, an internal control such as thegroup average or group centroid, which we call for

Fig. 3 Chlorine (Cl) content ofAmanitales compared to that ofother orders and of someAmanita (A) species comparedto the references. CI Confidenceinterval

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simplicity the reference fungus, is a useful tool to detectmajor deviations of selected samples from the mean valuesof the dataset, and allows within and among groupcomparisons of the values measured. In our opinion, this

methodology could be applied to any data that can besummarised by descriptive statistics, including morpholog-ical or ecological characters. The use of the group centroidmay be of interest also in multivariate analyses, although in

Fig. 4 Selenium (Se) content ofBoletales compared to that ofother orders and of someBoletus species compared to thereferences and to species ofLycoperdon (L), Suillus (S), andXerocomus (X). CI Confidenceinterval

Fig. 5 Classification of ordersby multidimensional scaling(MDS) using all chemicalelements studied as variables.Stress of final configuration:0.0289. Square Referencefungus

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such conditions it will only provide an illustration of thetrend of the data analysed for a given dataset. The internalcontrols must be defined on a case-by-case basis: in ouranalysis, we have found useful to first define the overallcentroid by computing the average values for each elementover the complete dataset (8,999 records) and then tocompute the centroids of each order.

By no means, however, does the reference funguscorrespond to or can replace the type species concept. Itdescribes the statistical width of one or more characters andas such will contribute to better define taxa, at the sametime helping to decide whether or not an unidentifiedsample may or may not belong to a given dataset/species.

Our study has several limitations. First, the inhomoge-neous and somewhat random structure of the sampling doesnot allow us to generalise the results or to draw any firmtaxonomic conclusions from our work. In fact, some of thegroupings seen in our multivariate analysis may be artefactscaused by the non-random sampling that has led to thepresent structure of the database. In fact, most of oursamples originate from only one country, and we cannotapply our results with certainty to any other dataset. Inaddition, mathematical constraints have influenced ourchoice of models, leading to the use of those taxa forwhich enough samples would be available for a meaningfulstatistical analysis. Finally, the method used for the

chemical analysis cannot be applied routinely to largesamples, although it works well with comparatively smallamounts of organic material, and the technical equipment isnot available in many taxonomy laboratories.

Nevertheless, the results from the MDS and discrim-inant analyses carried out on the Boletales suggest thatthe methodology might have useful applications intaxonomy. Vizzini et al. (2007), in fact, have reachedcomparable conclusions on the taxonomic and phyloge-netic relationship among B. aereus, B. aestivalis, B. edulisand B. pinophilus using molecular biology methods. Inaddition, the results of the chemical analyses are quiteconsistent, with comparatively small deviations amongsamples of the same species.

We have also been able to show that at least threedifferent ecological and geographical factors (origin, habitatand elevations), at least in the dataset investigated, have nosignificant influence on the content of chemical elements ofsamples belonging to the same taxon.

Taken together, the results of our investigations wouldsuggest that chemical elements are a useful tool for thetaxonomic characterisation of fungi and could be added tothe already existing arsenal of methods that, whencombined in a polyphasic taxonomy (Petrini LE and Petrini2005; Petrini O and Petrini 1996), will lead to a morecomprehensive classification of fungal taxa.

Original Predicted by analysis

B. aereus B. aestivalis B. edulis B. edulis group B. pinophilus

Boletus aereus (n =27) 25.9 7.4 11.1 40.7 14.8

B. aestivalis (n=34) 14.7 20.6 14.7 47.1 2.9

B. edulis (n =114) 0.0 0.9 71.1 20.2 7.9

B. edulis group (n=132) 0.0 0.8 18.9 78.0 2.3

B. pinophilus (n=82) 2.4 0.0 8.5 2.4 86.6

Table 2 Percentage of casescorrectly identified by canonicaldiscriminant analysis

69.2% of all cases were correct-ly identified.

Fig. 6 Classification of selectedspecies of Boletales by multidi-mensional scaling (MDS) usingall chemical elements studied asvariables. Stress of final configu-ration: <0.005. BA Boletusaereus, BC B. calopus, BE B.edulis, BG B. edulis group, BHB. rhodopurpureus, BL B.luridus, BP B. pinophilus, BRBoletales, BS B. aestivalis, BV B.pulverulentus, LD Lecciniumduriusculum, RM Reference fun-gus, RR Russulales, SG Suillusgranulatus, SL S. luteus, XRXerocomus rubellus, XS X.subtomentosus

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