Yeast volatomes differentially effect larval feeding in an ... · Ljunggren et al. - p. 4 68 Plants...

Yeast volatomes differentially effect larval feeding in an 1

insect herbivore 2

Joel Ljunggren,a Felipe Borrero-Echeverry,

b* Amrita Chakraborty,

b** Tobias U. 3

Lindblom,b***

Erik Hedenström,a Maria Karlsson,

c Peter Witzgall,

b# Marie 4

Bengtssonb#

5

6

aDept. Chemical Engineering, Mid Sweden University, Sundsvall, Sweden 7

bDept. Plant Protection Biology, Swedish University of Agricultural Sciences, 8

Alnarp, Sweden 9

cDept. Horticulture, Swedish University of Agricultural Sciences, Alnarp, Sweden 10

11

Running head: Yeast volatomes and insect attraction 12

13

#Address correspondence to Marie Bengtsson, [email protected] and Peter 14

Witzgall, [email protected]. 15

*Present address: Felipe Borrero-Echeverry, Corporación Colombiana de 16

Investigación Agropecuaria – AGROSAVIA, Mosquera, Colombia 17

**Present address: EVA Unit, Faculty of Forestry and Wood Sciences, Czech 18

University of Life Sciences, Prague, Czech Republic 19

***Present address: Dept. Crop Production Ecology, Swedish University of 20

author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was not peer-reviewed) is the. https://doi.org/10.1101/721845doi: bioRxiv preprint

https://doi.org/10.1101/721845

Ljunggren et al. - p. 2

Agricultural Sciences, Ultuna, Sweden 21

J.L. and F.B.-E. contributed equally to this work 22

23

ABSTRACT Yeasts form mutualistic interactions with insects. Hallmarks of this 24

interaction include provision of essential nutrients, while insects facilitate yeast 25

dispersal and growth on plant substrates. A phylogenetically ancient, chemical 26

dialogue coordinates this interaction, where the vocabulary, the volatile chemicals 27

that mediate the insect response, remains largely unknown. Here, we employed gas 28

chromatography-mass spectrometry (GC-MS), followed by hierarchical cluster 29

(HCA) and orthogonal partial least square discriminant analysis (OPLS-DA), to 30

profile the volatomes of six Metschnikowia spp., Cryptococcus nemorosus and 31

brewer's yeast Saccharomyces cerevisiae. The yeasts, which are all found in 32

association with insects feeding on foliage or fruit, emit characteristic, species-33

specific volatile blends that reflect the phylogenetic context. Species-specificity of 34

these volatome profiles aligned with differential feeding of cotton leafworm larvae 35

Spodoptera littoralis on these yeasts. Bioactivity correlates with yeast ecology; 36

phylloplane species elicited a stronger response than fruit yeasts, and larval 37

discrimination may provide a mechanism for establishment of insect-yeast 38

associations. The yeast volatomes contained a suite of insect attractants known from 39

plant and especially floral headspace, including (Z)-hexenyl acetate, ethyl (2E,4Z)-40

deca-2,4-dienoate (pear ester), (3E)-4,8-dimethylnona-1,3,7-triene (DMNT), linalool, 41

α-terpineol, β-myrcene or (E,E)-a-farnesene. A wide overlap of yeast and plant 42

volatiles, notably floral scents further emphasizes the prominent role of yeasts in 43

plant-microbe-insect relationships including pollination. The knowledge of insect-44


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yeast interactions can be readily brought to practical application, live yeasts or yeast 45

metabolites mediating insect attraction provide an ample toolbox for the 46

development of sustainable insect management. 47

IMPORTANCE Yeasts interface insect herbivores with their food plants. 48

Communication depends on volatile metabolites, and decoding this chemical 49

dialogue is key to understanding the ecology of insect-yeast interactions. This study 50

explores the volatomes of eight yeast species which have been isolated from foliage, 51

flowers or fruit, and from plant-feeding insects. They each release a rich bouquet of 52

volatile metabolites, including a suite of known insect attractants from plant and 53

floral scent. This overlap underlines the phylogenetic dimension of insect-yeast 54

associations, which according to the fossil record, long predate the appearance of 55

flowering plants. Volatome composition is characteristic for each species, aligns with 56

yeast taxonomy, and is further reflected by a differential behavioural response of 57

cotton leafworm larvae, which naturally feed on foliage of a wide spectrum of broad-58

leaved plants. Larval discrimination may establish and maintain associations with 59

yeasts and is also a substrate for designing sustainable insect management 60

techniques. 61

KEYWORDS Yeast volatome, metabolomic profile, floral odorants, chemical 62

signals, larval attraction, olfaction, Noctuidae, Lepidoptera 63

64

Microorganisms essentially interface plants and insects (1-4). Invisibly, 65

microorganisms broadcast a rich bouquet of volatile metabolites to mediate 66

communication with other microorganisms, plants and associated animals (5-7). 67


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Plants also release volatile compounds in abundance, but there is mounting evidence 68

that the production of volatiles by bacteria (8, 9), fungi (10-12) and yeasts (13-17) is 69

equally prolific. A wide overlap in compounds released by plants (18) and microbes 70

(19) suggests furthermore that plant headspace includes volatiles that are produced 71

by plant-associated epiphytic and endophytic microbes. A striking example is floral 72

scent, where bacteria and especially yeasts metabolize pollen, nectar and other floral 73

compounds and thus become a prominent source of volatiles (20-25). 74

Yeasts are widely associated with insects since they require vectors for dispersal and 75

outbreeding. In addition, larval feeding facilitates yeast growth on plant substrate. 76

Yeasts provide, on the other hand, nutritional services to insects (26-32). This 77

mutualistic interaction is facilitated by communication with volatile metabolites. 78

Yeasts have apparently evolved the capacity to synthesize aroma compounds to 79

attract insects (33-35) and insects, on the other hand, possess dedicated olfactory 80

receptors tuned to yeast fermentation metabolites that signal suitable substrates for 81

adult and larval feeding (36-39). Consequently, yeast volatiles, in addition to plant 82

volatiles, play a part in host-plant and food finding in insect herbivores, including 83

flies and moths (5, 40-44). 84

Investigations of the volatile metabolites of insect-associated yeasts serve a dual 85

purpose. Plants and their insect herbivores are fundamental to many ecosystems. 86

Olfactory recognition of food plants by insects is key to their interactions (45-47), 87

and it is, accordingly, of fundamental interest to identify the microbial component of 88

plant-insect communication. Furthermore, yeast metabolites or live yeasts facilitate 89

insect management. Lack of environmentally benign, yet efficient control methods is 90

an increasingly pressing issue in times of global change and increasing food 91


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insecurity (48-52). Yeast attraction of insects and their larvae for feeding (33, 44, 53-92

56) can be exploited for population control of herbivores (57, 58), as well as for 93

improved crop pollination (59). 94

We asked whether taxonomically related yeasts, isolated from different insects and 95

habitats, differ with respect to their volatile metabolomes, and whether cotton 96

leafworm larvae behave differently towards them. We selected a Cryptococcus and 97

several Metschnikowia yeasts, which have been isolated from insect larvae feeding 98

on fruit or foliage, including the cotton leafworm, Spodoptera littoralis, a 99

polyphagous noctuid moth (60). We have investigated the volatomes of these yeasts 100

by gas chromatography-mass spectrometry (GC-MS) and comparative multivariate 101

discriminant analysis, affording unique volatile fingerprints. Differential larval 102

attraction reveals the behavioural relevance of characteristic differences in yeast 103

volatome composition. 104

RESULTS 105

Yeast headspace analysis. A phylogenetic tree of the yeasts investigated, 106

Cryptococcus nemorosus, six Metschnikowia spp. and baker's yeast Saccharomyces 107

cerevisiae is shown in Figure 1. These yeasts have all been found to occur in 108

association with insects. The volatiles released during fermentation were investigated 109

by GC-MS, and shown to contain a range of compounds, including largely methyl 110

and ethyl esters but also terpenoids, straight and branched alcohols, aldehydes, 111

ketones, acids, five sulfur and three nitrogen-containing volatiles (Figure 2, 112

Supplemental Table S1). Twenty-six of the 192 compounds found are not yet listed 113

in databases of volatiles from yeasts, fungi and bacteria, and 33 compounds are new 114


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for yeasts (17, 19). Many of these yeast-produced compounds, including terpenoids 115

such as linaool and farnesenes, and esters, such as pear ester, have also been found in 116

plant headspace (18). 117

Figure 2 compares the volatomes of these eight yeasts. Variation across replicates is 118

substantial, despite rigorous protocols employed for yeast growing and headspace 119

collection. However, species could still be separated according to headspace 120

composition by a discriminant analysis (OPLS-DA M1, R2X(cum) = 0.768; R

2Y(cum) = 121

0.918; Q2

(cum) = 0.756) resulting in 7 predictive components that explain 63% of the 122

entire variation. Especially after grouping compounds into 14 groups by hierarchical 123

cluster analysis (HCA) using the M1 loadings, Figure 2 further visualises that 124

headspace composition is characteristic for each yeast. 125

Headspace composition further reflects taxonomic position. M. andauensis, M. 126

fructicola and M. pulcherrima share morphological and physiological characters, and 127

the D1/D2 domain differs only with respect to few nucleotides (61-63). The close 128

relation between these three species (Figure 1) is in line with their volatome 129

composition, in comparison with the more distantly related Metschnikowia species 130

(Figures 2-3). 131

Headspace composition also helped to clarify the taxonomic status of a yeast 132

collected from apple, which had been tentatively and incorrectly determined as 133

Cryptococcus tephrensis, according to morphological criteria. Visual inspection of 134

its volatome fingerprint suggested this yeast to be closely related to M. fructicola 135

(replicates 7 to 12 of M. fructicola, Figure 2). This was then confirmed by 136


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sequencing the D1/D2 LSU rRNA gene, showing 99% similarity with the sequence 137

obtained from M. fructicola (NCBI accession number KC411961, Figure 1). 138

A three-dimensional score plot of the first three predictive components of M1 show 139

that M. hawaiiensis and M. saccharicola clearly separate according to the first three 140

dimensions and that the other species are clustering with little overlap (Figure 3). 141

The remaining species diverged in the remaining dimensions and by HCA of M1 142

scores (data not shown). Internal model robustness validation was performed by 143

randomly excluding three observations for each yeast. So as to keep at least three 144

observations, only one replicate was removed for M. andauensis and S. cerevisiae 145

was removed completely. Excluded observations were thereafter used as prediction 146

set in a new model made of the remaining observations [OPLS-DA M2, R2X(cum) = 147

0.686; R2Y(cum) = 0.879; Q

2(cum) = 0.596]. A zero misclassification error (Fishers 148

probability = 2.8 × 10-10

) further corroborated the robust ability of OPLS-DA to 149

distinguish between yeast headspace profiles. 150

M. hawaiiensis, M. saccharicola and M. lopburiensis. M. hawaiiensis has been 151

isolated from morning glory flowers and is associated with drosophilid species (64), 152

and M. saccharicola and M. lopburiensis have been found on sugarcane and rice 153

leaves (65). 154

M. hawaiiensis and M. saccharicola were the most prolific producers of volatiles, 155

several of which were not present in the other yeasts studied (Figure 2). They 156

separated clearly, according to OPLS-DA, from each other and the other yeasts 157

(Figure 3). The headspace of these two species has not yet been studied and contains 158

a number of compounds which are new to databases of yeast volatiles (Supplemental 159


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Table S1; 17, 19). They also contained several yet unknown compounds, which were 160

not found in commercial or our own libraries, and which did not match commercially 161

available standards. 162

Characteristic compounds for M. saccharicola were a range of putative 163

sesquiterpenes and also pear ester, a characteristic odorant of pear (66, 67) which is 164

also a strong bisexual attractant for codling moth Cydia pomonella (68-70). Indole, a 165

nitrous compound, was released by both M. lopburiensis and M. pulcherrima. 166

Methanol, ethyl (E)-2-methylbut-2-enoate and ethyl furan-3-carboxylate are the 167

primary class separators for M. lopburiensis. Methanol was also consistently found 168

in M. saccharicola samples (Figure 2, Supplemental Table S1). 169

The volatome of M. hawaiiensis was clearly separated from the other Metschnikowia 170

spp. (Figures 2, 3), methyl esters were key compounds in headspace class separation 171

(Supplemental Table S1). Perhaps coincidentally, two sulphur-containing 172

compounds, methyl 3-methylthio-propanoate and 3-methylsulfanylpropan-1-ol, 173

which are typical for M. hawaiiensis, are associated with the aroma of pineapple (71, 174

72). 175

M. andauensis, M. fructicola and M. pulcherrima. These very closely related 176

species (Figure 1; 63) are morphologically and ecologically similar. They have all 177

been found in larval frass of lepidopteran larvae (41, 62). Three compounds that 178

differentiate M. fructicola from other yeasts were 2-phenyl ethanal, 3-ethoxy-propan-179

1-ol and 3-metylbutan-1-ol. The top four discriminating compounds for M. 180

pulcherrima were ethyl 3-methylbutanoate, ethyl propanoate, nonan-2-ol and 181

sulcatone, which showed a high correlation with butyl butanoate. Two methyl-182


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branched short chain carboxylic acids, heptan-4-ol and unknown 147 were highly 183

characteristic for M. andauensis (Figure 2, Supplemental Table S1). 184

Cryptococcus nemorosus. Cryptococcus is polyphyletic and several species such as 185

C. nemorosus have been isolated from the plant phyllosphere and soil (73, 74). Ethyl 186

(E)-2-methylbut-2-enoate, aliphatic ketones, and aliphatic methyl-branched primary 187

alcohols were the main volatiles that separate C. nemorosus from the other species. 188

Strong correlations were observed for 6,10-dimethyl-5,9-undecadien-2-ol (fuscumol) 189

and its respective ketone, 6,10-dimethyl-5,9-undecadien-2-one (geranyl acetone). 190

Shared structures for classifying other species were also observed, namely 2-191

pentylthiophene was shown to be highly correlating with class membership of M. 192

andauensis (Supplemental Table S1). 193

Larval feeding on live yeasts. We next investigated attraction and feeding of S. 194

littoralis larvae in a choice test. Larval feeding was assayed in a petri dish with two 195

drops of liquid medium, one with live yeast and the other without. Three yeasts, M. 196

andauensis (p < 0.05), M. pulcherrima (p = 0.031) and S. cerevisiae (p = 0.002) 197

deterred feeding, more larvae fed on blank medium in their presence. Two species, 198

M. fructicola (p = 0.06) and M. saccharicola (p = 0.096) had no significant effect, 199

but M. hawaiiensis (p < 0.05), M. lopburiensis (p = 0.012) and C. nemorosus (p = 200

0.002) elicited larval attraction and feeding (Figure 4a). 201

An orthogonal partial least squares discriminant analysis (OPLS-DA) was used to 202

explore the correlation of yeast volatiles from different species with respect to 203

behavioural activity. Three classes, shown in Figure 4b, were used which resulted in 204

a model with 2 predictive and 5 orthogonal components [OPLS-DA M3, R2X(cum) = 205


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0.68; R2Y(cum) = 0.947; Q

2(cum) = 0.812). Model M3 showed excellent classification 206

performance (Fishers probability = 2.5 × 10-19

). When plotting the two OPLS-DA 207

predictive components, three groups separate clearly, showing that these yeasts can 208

be distinguished with respect to their behavioural effect (Figure 4b). 209

Among the eight yeast species, M. andauensis and C. nemorosus exhibited the 210

strongest activity, resulting in larval avoidance and feeding, respectively (Figure 4a). 211

The volatile profiles of these yeasts show considerable overlap with the other species 212

(Figure 1) and we hypothesized that volatiles released by the other species could be 213

used for sifting inactive volatile constituents and thus facilitate the search for 214

bioactive candidate compounds. We constructed two models to this purpose. 215

Volatiles of all species except M. andauensis were modelled against C. nemorosus, 216

eliciting the highest rate of feeding which resulted in a model with 2 predictive and 4 217

orthogonal components [OPLS-DA M4, R2X(cum) = 0.608; R

2Y(cum) = 0.984; Q

2(cum) = 218

0.933)]. Metschnikowia andauensis, which strongly deterred larvae from feeding, 219

was likewise modelled against all other species except C. nemorosus [OPLS-DA 220

M5, R2X(cum) = 0.69; R

2Y(cum) = 0.983; Q

2(cum) = 0.572]. Using M4 and M5, a shared 221

and unique structure (SUS) plot was made to illustrate key compounds that are, 222

compared to the other species, released in smaller or larger amounts by M. 223

andauensis and C. nemorosus. The SUS-plot (Figure 5) assigns two acids, several 224

methyl branched esters, camphene and two unknown compounds 132 and 147 to M. 225

andauensis, and geranyl acetone, cyclohexanone, 2-ethyl-1-benzofuran and 1,3,5-226

undecatriene to C. nemorosus. 227


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DISCUSSION 228

The yeasts studied here occur on plants, and in connection with insect larvae feeding 229

on these plants. A rich volatome found in all eight species may serve interactions 230

within and between microbial taxa. Presence of many odor-active compounds also 231

supports the idea that yeasts require animal vectors for dispersal and outbreeding. 232

Unlike fungal spores, yeast spores are not adapted for wind-borne transmission. 233

Needle-shaped ascospores, which are frequently found in the Metschnikowia clade, 234

promote dispersal by flower-visiting flies, beetles and bees. Yeasts, on the other 235

hand, provide nutritional services to insect larvae and adults (26, 27, 30, 31, 33, 40, 236

75-78). 237

Larvae of cotton leafworm S. littoralis that naturally feed on foliage of a broad range 238

of annual plants (79, 80) were attracted to volatiles of three yeasts (Figure 4). Figure 239

2 illustrates that yeast headspace is at least as rich and complex as headspace of their 240

food plants (91, 92), and that also many yeast compounds, including terpenoids, are 241

shared by these plants. This raises the question whether larvae of insect herbivores 242

become attracted to plant or to yeast odour for feeding, or both. Especially for insect 243

species found on a range of plant species, such as S. littoralis, volatiles from plant-244

associated yeasts may be sufficiently reliable signals, especially when these yeasts 245

are part of the larval diet. 246

The question to which extent yeast vs plant volatiles contribute to oviposition and 247

larval feeding has been formally addressed in Drosophila melanogaster, where 248

brewer's yeast headspace alone elicits attraction and oviposition. Drosophila larvae 249

complete their entire development on yeast growing on minimal medium, which 250


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supports the conclusion that the fruit merely serves as a substrate for yeast growth 251

(40). In comparison, strict dissection of plant and microbial components is 252

experimentally difficult in insects that require foliage for feeding. For example, 253

grape moth Paralobesia viteana was attracted to grape leaves after washing off 254

microbial colonies, but the participating role of microbes remaining on foliage or 255

endophytes is yet unresolved (93). 256

A closer look at attractants identified from plant hosts produces a surprising insight: 257

typical plant volatiles such as (Z)-3-hexenyl acetate, linalool, nonanal or even (3E)-258

4,8-dimethylnona-1,3,7-triene (DMNT), which play an important role in attraction of 259

P. viteana or the grape berry moth Lobesia botrana, are all produced by several 260

yeasts (Figure 2, 93, 94). Likewise, compounds from cotton headspace that elicit 261

antennal or behavioral responses in cotton leafworm S. littoralis are also produced by 262

yeasts (Figure 2, 91, 95). Among these is again DMNT. Induced release of DMNT 263

from plants following herbivore damage attracts natural enemies and deters some 264

insect herbivores. In cotton leafworm, upwind flight to sex pheromone and cotton 265

volatiles is suppressed by large amounts of DMNT, due to its prominent effect on 266

central olfactory circuits (47, 92, 96). 267

DMNT is also a floral scent component, across a wide range of plants (97) and an 268

attractant of flies and moths (94, 98-100). Yeasts obviously contribute to DMNT 269

release from flowers, since DMNT was found in all yeasts studied here (Figure 2). 270

Besides DMNT, a wide range of volatiles co-occurs in yeasts and angiosperm 271

flowers, for example the typical Drosophila attractants acetoin, ethanol, ethyl 272

acetate, 2-phenylethyl acetate, 2-phenylethanol (Figure 2; 101). 2-phenylethanol, a 273

typical yeast odorant (e.g. 102), is also produced by green plants (e.g. 103). Let alone 274


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an overlap of compounds produced by both plants and yeasts, fumigation of 275

elderberry flowers with broad-spectrum antibiotics revealed that floral phyllospheric 276

microbiota are unique producers of key floral terpenes (20). The yeasts investigated 277

here all produce a range of terpenes (Figure 2, Supplemental Table S1). 278

Insect-yeast chemical communication has evolved long before the emergence of 279

flowering plants. Fungivory and herbivory on plants was initiated during the Early 280

Devonian ~400 Ma, concurrent with the appearance of budding yeasts and prior to 281

angiosperm pollination syndromes during the Cretaceous ~100 Ma (104-107). This 282

lends support to the idea that a sensory bias for yeast-produced compounds, together 283

with ubiquitous presence of yeasts in flowers, has contributed to the evolution of 284

floral scent and insect-mediated pollination (23, 24, 101, 108, 109). 285

While the ecological and evolutionary consequences of chemical dialogue between 286

plants, microbes and insects are unequivocal, it is yet largely unclear which of the 287

many volatiles released by yeasts encode this interaction. A comprehensive analysis 288

of yeast volatomes is a first and necessary step towards identifying the active 289

compounds. Thirty-three of the 192 volatiles (Figure 2, Supplemental Table S1) are 290

new for yeasts. Most of them were released by M. hawaiiensis M. lopburiensis and 291

M. saccharicola, which are the most recently discovered species (64, 65). The 292

database of yeast volatiles creates a basis for future studies, aimed at functional 293

characterization of insect olfactory receptors and attraction bioassays, towards the 294

identification of the behaviourally active compounds (110-112). 295

The overall species-specific volatome patterns showed variation between replicates, 296

even though growth conditions were strictly controlled and sampling intervals 297


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adjusted to cancel out growth stage variations (Figure 2). A general assumption in 298

metabolomics is that identical genotypes produce the same steady state metabolite 299

concentrations under stringent conditions, while metabolic snapshots often show 300

considerable biological variability. Metabolite-metabolite correlations derived from 301

enzymatic reaction network activity may nonetheless be robust, despite considerable 302

intrinsic, stochastic variation of metabolite concentrations obtained at momentary 303

peeks into the state of an organism (113-115) 304

In spite of inherent variation among volatile samples, numerical headspace analysis 305

by OPLS-DA followed by HCA revealed characteristic volatile fingerprints for each 306

of the eight yeasts (Figures 2, 3) which align with the phylogenetic analysis based on 307

sequences from the D1/D2 region (Figure 1) and yeast taxonomy and ecology 308

(Figure 1; 63, 76). Moreover, we found that OPLS-DA exhibited a robust yeast-309

species assignment headspace samples and is therefore a useful tool for studying and 310

classifying unknown species with regard to their volatiles (Figure 3). 311

Volatile fingerprinting or chemotyping has previously been shown to differentiate 312

between ectomycorrhizal, pathogenic and saprophytic fungi, as a complement to 313

genotyping (116, 117). This was confirmed by comparing M. fructicola and M. 314

andauensis, which are taxonomically close and difficult to discriminate according to 315

genotyping (Figure 1; 118). They quantitatively and clearly separated according to 316

headspace proportions, in addition to production of methanol by M. fructicola 317

(Figures 2, 3). Further support for the use of volatomes in species discrimination 318

comes from an isolate from codling moth larvae, which had been misidentified as C. 319

tephrensis. Comparison of headspace data with M. fructicola evidenced overlap of 320

101 compounds with significant coefficient values and non-zero confidence interval 321


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for the whole dataset. Subsequent DNA analysis identified this yeast as M. fructicola 322

(Figure 1). 323

The species-specific volatome differences are corroborated by a selective larval 324

feeding response (Figure 4), where cotton leafworm larvae, which are typical foliage 325

feeders, prefer phyllosphere yeasts over the yeasts associated with fruit and 326

frugivorous insects. Larvae avoided baker's yeast commonly found with D. 327

melanogaster and M. andauensis and M. pulcherrima which have been isolated from 328

codling moth, Cydia pomonella, feeding in apple (41). It is yet unknown whether 329

cotton leafworm forms yeast associations with yeasts in natural habitats, but a 330

consistent larval response to yeasts may establish and sustain such associations. 331

Identifying behaviorally active metabolites is key to understanding the ecology of 332

insect-yeast interactions. Geranyl acetone, an aggregation pheromone component of 333

C. pomonella larvae (119) is a distinctive compound for C. nemorosus (Figures 2, 5), 334

which elicited the strongest larval feeding response (Figure 4). Among the cotton 335

leafworm olfactory receptors which have been functionally characterized, several are 336

tuned to compounds produced by yeasts, and some even elicited larval attraction as 337

single compounds, such as benzyl alcohol, benzaldehyde or indole (120). For a more 338

complete behavioral identification, it would probably be necessary to test compound 339

blends, including candidate compounds from the headspace of M. hawaiiensis, M. 340

lopburiensis or C. nemorosus (Figures 2, 4, 5). 341

At the same time, our study reveals potential antifeedants. Camphene has indeed 342

already been reported as a repellant in S. littoralis (121) and its acute larval toxicity 343

has been shown in the sister species S. litura (122). In addition, S. littoralis females 344


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detect camphene, as well as 3-methylbutyl acetate (123), both of which are sign 345

compounds for M. andauensis (Figures 2, 4, 5). Discriminant analysis points towards 346

presence of attractive and antagonistic yeast volatiles and highlights compounds for 347

future screening assays. 348

Cotton leafworm is polyphagous on a variety of crops including vegetables in the 349

Afrotropical and western Palearctic. Its sister species S. litura is found over Asia, 350

Australasia, and Oceania and the South-American species S. frugiperda has recently 351

invaded Africa (52, 60, 79, 124). Global change and increasing food insecurity 352

render insect control an ever more challenging and urgent task (51, 125-127). 353

Detrimental environmental and health effects warrant downregulation of 354

conventional pesticides and accentuate the further development of biological insect 355

control, comprising natural antagonists, insect pathogens or semiochemicals. 356

Semiochemicals and pathogens are widely and successfully used as stand-alone 357

techniques (128, 129), but semiochemicals could be combined with pathogens into 358

lure-and-kill strategies (57, 58, 130). Current use of insect semiochemicals is based 359

on controlled release formulations of synthetic chemicals, while yeasts could be used 360

for live production of insect attractants (5, 131) 361

That yeasts would make suitable producers of insect attractants is supported by 362

establishment of biofilms with strong survival ability, which enables postharvest 363

control of fungal diseases in fruit (132-134). Combination of attractant yeasts for 364

targeted ingestion of an insect baculovirus or a biological insecticide has been 365

successful in laboratory and first field experiments, against codling moth and spotted 366

wing Drosophila (130, 135, 136). For further improvement, identification of key 367


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compounds mediating insect attraction will facilitate selection of yeast species and 368

strains. 369

Yeast volatiles are also antifungal (132, 133) and may directly, or through other 370

members of the plant microbiome, impact on plant fitness. A critical component of 371

functional interlinkages betwen plants and an ensemble of associated microbiota is 372

that the plant immune system reliably differentiates between synergistic and 373

antagonistic microbes (137, 138). Odorants are essential in regulating mutual and 374

detrimental colonizers in plant microbial networks (6, 7, 139) and yeast volatiles are 375

obviously involved in this chemical dialogue, since compounds such as farnesol or 2-376

phenylethanol participate in quorum sensing and interspecies interactions (Figure 2, 377

Supplemental Table 1; 16, 140). Integrating plant microbiomes in crop protection 378

concepts, for insect control, enhanced stress tolerance and disease resistance is a 379

future challenge in agriculture (141). 380

MATERIALS AND METHODS 381

Yeasts. Metschnikowia yeasts were purchased from the CBS-KNAW collection 382

(Utrecht, Netherlands), except M. fructicola, which was isolated from apple (Alnarp, 383

Sweden) infested with larvae of codling moth Cydia pomonella (Lepidoptera, 384

Tortricidae), Cryptococcus nemorosus was isolated from cotton leafworm 385

Spodoptera littoralis (Lepidoptera, Noctuidae) larvae (laboratory rearing, Alnarp, 386

Sweden), and Saccharomyces cerevisiae was obtained from Jästbolaget AB 387

(Sollentuna, Sweden). 388

M. andauensis, M. fructicola and M. pulcherrima were found in guts and larval feces 389

of caterpillars feeding on maize, corn earworm Helicoverpa armigera (Lepidoptera, 390


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Noctuidae) and European corn borer Ostrinia nubilalis (Lepidoptera, Crambidae) 391

(62). M. andauensis and M. pulcherrima, and occasionally M. fructicola were found 392

in apple and larval feces of codling moth Cydia pomonella (Lepidoptera, Tortricidae) 393

(41). M. saccharicola, M. lopburiensis were isolated from foliage in Thailand (65) 394

and M. hawaiiensis from fruit flies (Drosophilidae, Diptera) (64). 395

DNA isolation and yeast identification. Genomic DNA was isolated from 396

overnight yeast cultures grown in liquid yeast extract peptone dextrose (YPD) 397

medium. 2 mL of the overnight cell cultures were pelleted (13.000 rpm for 1 min) 398

and washed with sterile ddH2O. The pellets were resuspended in 200 μL lysis buffer 399

(2% Triton X-100, 1% SDS, 0.1 M NaCl, 10 mM Tris, 1 mM EDTA, pH 8), and 200 400

μL phenol:chloroform:isoamyl alcohol (25:24:1) mixture. The glass beads (200 µL) 401

were then added to the tubes and vortexed thoroughly for 3 min. To this mixture, 200 402

μL TE buffer (10 mM Tris-Cl, 1 mM EDTA; pH 8.0) was added and centrifuged at 403

13.000 rpm for 10 min. The upper aqueous phase was collected and 10 μL of 404

RNaseA (10 mg/mL) was added and incubated at 37°C during 45 min. The DNA 405

was precipitated using 300 mM sodium acetate, three volumes of cold absolute 406

ethanol (99.9%) and centrifuged at 13.000 rpm for 10 min at 4°C. The DNA pellet 407

was then washed in 70% cold ethanol (13.000 rpm for 10 min, 4°C), air-dried, and 408

re-suspended in 30 μL TE buffer and stored at -20°C until use. 409

The D1/D2 domains of the 26S ribosomal RNA gene was amplified with the 410

universal primer pair NL-1 and NL-4 and the internally transcribed spacer (ITS) 411

region with the primer combination ITS-1 and ITS-4 (142, 143). The PCR reaction 412

and product visualisation on agarose gel was performed as previously described 413

(101). PCR-products were purified using ExoStar-IT (USB Corporation, USA) 414


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following the manufacturer's protocol sequenced using BigDye v.1.1 terminator 415

sequencing kit in an ABI PRISM 3130 genetic analyser (Applied Biosystems, New 416

Jersey, US). 417

All sequences were aligned in the program Bioedit 7.0.9.0 Sequence Alignment 418

Editor (144). Each sequence was tested for identity and similarity against sequences 419

deposited in the National Center for Biotechnology Information (NCBI) using 420

Megablast-search (accession number KF839191, KC411961). Only similarities over 421

95% were considered. The phylogenetic tree of the yeast species investigated, based 422

on nucleotide sequences of the D1/D2 domain of 26S rDNA, was constructed using 423

the neighbor-joining (NJ) method in MEGA 7.0 (145). The NJ method, based on the 424

evolutionary distance data that minimizes the total branch length during clustering of 425

operational taxonomic units (OTUs), is efficient and reliable for phylogenetic 426

reconstructions (146). The evolutionary distances were calculated according to the 427

Jukes and Cantor (JC) substitution model to minimize the bias due to nucleotide 428

substitution during divergence. The JC substitution model considers the rate of 429

substitution frequencies of all pairs of four nucleotides (A, T, G, C) to be equal 430

(147). The bootstrap values for the phylogenetic tree reconstruction were determined 431

from 1.000 replications and are given next to the branch (Figure 1). 432

Headspace collection and chemical analysis. Yeasts were grown in 100 mL liquid 433

minimal medium (148) in 250-mL culture flasks, during 24 h in a shaking incubator 434

(25°C, 260 rpm). Yeast headspace was collected by drawing charcoal-filtered air 435

(0.125 L/min), through a 1-L gas wash bottle containing the yeast broth, over a 35-436

mg Super Q trap (80/100 mesh; Alltech, Deerfield, IL, USA), which was held 437

between plugs of glass-wool in a 4 x 40-mm glass tube. Collections were done for 438


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ca. 24 h, at 20 to 22 °C and 10 to 30 Lux. The charcoal filter (50 g activated 439

charcoal) for incoming air and the Super Q trap were connected with glass fittings to 440

the wash bottle. All glassware was heated to 375°C for 10 h before use (149). 441

Following volatile collections, the trap was extracted with 0.5 mL of redistilled 442

hexane. Sample volumes were reduced to ca. 50 µL, at ambient temperature in 443

Francke-vials with an elongated tip (5 cm x 2 mm i.d.). Samples were stored in 444

sealed glass capillary tubes at -19°C. The Super Q trap was wrapped in aluminium 445

foil for protection from light. Before use, it was rinsed sequentially with 3 mL of 446

methanol (redistilled >99.9% purity, Merck, Darmstadt, Germany) and hexane 447

(redistilled >99.9% purity; Labscan, Malmö, Sweden). 448

Yeast headspace collections were analysed on a coupled gas chromatograph–mass 449

spectrometer (GC–MS; 6890 GC and 5975 MS; Agilent Technologies, Palo Alto, 450

CA, USA), operated in the electron impact ionization mode at 70 eV. The GC was 451

equipped with fused silica capillary columns (30 m x 0.25 mm, d.f. = 0.25 µm), DB-452

Wax (J&W Scientific, Folsom, CA, USA) or HP-5MS (Agilent Technologies). 453

Helium was used as the mobile phase at an average linear flow rate of 35 cm/s. Two 454

µL of each sample were injected (splitless mode, 30 s, injector temperature 225°C). 455

The GC oven temperature for both columns was programmed from 30°C (3 min 456

hold) at 8°C/min to 225°C (5 min hold). 457

Data were exported in NetCDF file format and deconvoluted into compound spectra, 458

elution profile and peak area. We used MS-Omics software (Vedbaek, Denmark) and 459

the PARAFAC2 model (150), and the non-commercial package HDA (version 0.910, 460

P. Johansson, Umeå University, Sweden), based on the H-MCR method (151). Both 461


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methods utilize covariation between samples to separate co-eluting components, and 462

to pool mass spectra across samples affording unambiguous spectra even at low 463

signal to noise ratios. Approx. 70% and 30% of the peaks were separated by 464

PARAFAC2 and H-MCR, respectively. However, neither deconvolution method 465

produced satisfactory results for all compounds, which necessitated manual selection 466

of the most feasible method in some cases. 467

Compounds were identified according to their retention times (Kovat’s indices) and 468

mass spectra, in comparison with the National Institute of Standards and Technology 469

(NIST, version 14) mass spectral library and authentic standards, on two columns. 470

Extra care was taken to verify the identity of compounds showing high variation in 471

abundance between yeast species. Compounds present in blank recordings of the 472

growth medium were subtracted. 473

Insects. A cotton leafworm Spodoptera littoralis (Lepidoptera, Noctuidae) 474

laboratory colony was established using field-collected insects from Alexandria 475

(Egypt) in 2010. This colony was interbred with wild insects from Egypt every year. 476

Insects were raised on a semisynthetic agar-based diet (152) under a 16L:8D 477

photoperiod, at 24oC and 50 to 60% RH. 478

Larval feeding assay. Yeasts (M. andauensis, M. fructicola, M. hawaiensis, M. 479

lopburiensis, M. pulcherrima, M. saccharicola, S. cerevisiae and C. nemorosus) 480

were grown in 125-mL culture flasks in 50 mL of liquid minimal medium (148) for 481

20 h in a shaking incubator (25 °C, 260 rpm). Optical density at 595 nm was between 482

1.5 and 1.8, and cell counts were adjusted to 1.5 x 107 cells/mL. 483


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A two-choice bioassay was conducted to determine neonate larval yeast attraction 484

and feeding. Two 50 µL drops of a 20-h old yeast culture and blank minimal medium 485

were pipetted opposite from each other, approx 1 cm from the edge of a plastic petri 486

dish (92 mm ø, No.82.1472, Sarstedt AG & Co., Nümbrecht, DE). Colorants, blue 487

and green, (Dr. Oetker Sverige AB, Göteborg, SE) were used at 1:10 dilution to color 488

yeast and minimal medium, in order to distinguish between the larvae that fed on 489

yeast medium, blank medium or both. Preliminary tests did not show a bias in larval 490

attraction to the different colorants (N=30; F=1.529; p=0.222; ANOVA). 491

Ten starved neonate larvae were collected 24 to 36 h after hatching and were placed 492

in the centre of the petri dish with a fine brush. The dish was covered with a lid to 493

prevent the larvae from escaping, and larvae were left to feed for 2 h. They were then 494

checked under a microscope for their gut coloration. Ten independent replicates with 495

10 neonate larvae were done for each yeast. The larvae response index (LRI) was 496

calculated from the number of larvae feeding on the yeast treatment (nY) and control 497

(nC): LRI = (nY-nC)/(nY+nC). 498

Statistical Analysis. All yeast species and volatile compounds were collated into a 499

matrix, containing 56 yeast headspace collections and the integrated areas of the 192 500

compounds found. Two pre-treatment methods were selected before building the 501

model. A logarithmic transformation of x-variables served to minimize skewness of 502

the variables. Since the abundance of compounds does not necessarily correlate with 503

biological activity, pareto scaling was used to augment the impact of compounds 504

present in very small amounts. Hierarchical cluster analysis (HCA), orthogonal 505

partial least square discriminant analysis (OPLS-DA) and partial least square 506

discriminant analysis (PLS-DA) and its corresponding validation tests were 507


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calculated with SIMCA 13.0.3 (Sartorius Stedim Data Analytics AB, Umea, 508

Sweden). 509

Three methods were used to validate the multivariate models. Internal cross 510

validation (CV) was done with eight CV-groups of dissimilar observations. A 511

permutation test, by randomization of the class vector, was used to test for the 512

presence of spurious correlations between volatile profiles and class membership by 513

fitting each permutation to a new PLS-DA model and observing the resulting 514

explained variance and predictive power. Finally, an internal validation set of 515

observations that spanned the multivariate space for each model was inspected for 516

any large deviations. 517

Larval feeding of S. littoralis on yeasts was compared using Student’s t-test, with the 518

level of significance set to p=0.05. 519

SUPPLEMENTAL MATERIAL 520

Supplemental material for this article may be found at … 521

SUPPLEMENTAL TABLE S1, PDF file, 0.15 MB. 522

ACKNOWLEDGEMENTS 523

This work was supported by the Linnaeus environment “Insect Chemical Ecology, 524

Ethology, and Evolution (IC-E3)” (Formas, SLU), Västernorrland County 525

Administrative Board, European Regional Development Fund of the European Union 526

and the Faculty of Landscape Architecture, Horticulture and Crop Production 527

Science (SLU, Alnarp). The authors gratefully acknowledge the Swedish 528


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Metabolomics Centre, Umeå for access to GC-MS evaluation software and helpful 529

discussions. 530

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Entomol 108:1345-1357. 947


https://doi.org/10.1101/721845


Figure legends 948

FIG 1 Phylogenetic tree of the yeasts used for volatile analysis (bold-faced) and 949

sequences deposited in the NCBI database, based on the nucleotide sequences of the 950

D1/D2 domain of the 26S rDNA, constructed according to the neighbor-joining 951

method with bootstrap values >50%. Asterisks denote the two isolates of M. 952

fructicola corresponding to replicates 1 to 6 and 7 to 12 in Figure 2. 953

FIG 2 Volatile compounds identified from headspace collections of fermenting 954

yeasts by GC-MS (see also Supplemental Table S1). Compounds were grouped 955

according to hierarchical cluster analysis (HCA), circles depict relative abundance 956

of compounds after normalization by abundance across species (rows) and 957

observations (columns). Yeast species listed according to the phylogenetic tree 958

(Figure 1). Abbreviations see Figure 1. 959

FIG 3 Groups of yeast volatiles according to orthogonal partial least square 960

discriminant analysis (OPLS-DA). The first three principal components represent 961

22.9 %, 14.7 % and 9.6 % of the total variation in the dataset of eight yeast species. 962

Abbreviations see Figure 1. 963

FIG 4 Larval feeding assay and class separation, according to orthogonal partial 964

least square discriminant analysis (OPLS-DA). (a) Bars show the response index RI 965

for larval attraction and feeding (RI>0) and avoidance (RI<0) in response to eight 966

yeasts. Asterisks show significance according to Student’s t-test (P<0.05 and P<0.01, 967

respectively); (b) OPLS-DA score plot of M3 with yeasts classified according to 968

larvae response. Component 1 and 2 are predictive. Yeasts separate according to 969


https://doi.org/10.1101/721845


behavioral effect, repellency, feeding and no effect. The outline ellipse shows 970

Hotelling’s T2 (95 %) limit. 971

FIG 5 Shared and unique structures plot (SUS-plot) featuring metabolites of the 972

most and least preferred yeasts for cotton leafworm larval feeding, C. nemorosus and 973

M. andauensis (Figure 4). Correlation from the predictive components of the two 974

models, Corr(tp,X), are plotted against each other. Unique volatiles (top left and 975

bottom right quadrants) are oppositely affected for both M. andauensis and C. 976

nemorosus. Compounds similarly affected in all yeasts are located along the diagonal 977

running through the shared effect quadrants. Unique, significant volatiles are shown 978

for M. andauensis (blue circles) and C. nemorosus (red circles). 979


https://doi.org/10.1101/721845

Metschnikowia fructicola (MF)**

M. fructicola (MF)*

M. andauensis (MA)

M. pulcherrima (MP)

M. saccharicola (MS)

M. lopburiensis (ML)

M. hawaiiensis (MH)

M. andauensis AJ745110

M. fructicola EU373454

M. pulcherrima KY108497

M. hawaiiensis KY108477

Saccharomyces cerevisiae JQ914745 (SC)

C. nemorosus (CN)

C. nemorosus KF830191

Cryptococcus tephrensis JQ688991

M. saccharicola AB697752

M. lopburiensis AB697756

100

100

98

100

100

100

100

100

100

100

53

0.05


https://doi.org/10.1101/721845

Unknown 170Unknown 175Unknown 177γ-Decalactone

Ethyl 3-methyltio-propanoateMethyl 2-methylpropanoate

Methyl hexanoateMethyl octanoate

Furan-2-carbohydrazideMethyl (E)-hex-2-enoate

Methyl 3-hydroxybutanoateMethyl 2-furoateMethyl benzoate

Methyl 3-methylthio-propanoateMethyl 2-phenylacetate

Methyl butanoateMethyl 3-methylpentanoateMethyl 2-methylbutanoateMethyl 3-methylbutanoate

Methyl 2-hydroxy-3-methylpentanoateMethyl 2-methylpentanoate

Methyl 2-hydroxy-3-methylbutanoateUnknown 96

4-Ethylbenzene-1,3-diolEthyl palmitate

Ethyl palmitoleate(E)-3-Octen-2-one

2-Phenyl ethanal(Z)-Hex-3-en-1-ol

1-Octen-3-olUnknown 84

BenzaldehydeUnknown 71

1-HexanolUnknown 90g-Isogeraniol

Nerol1-(Furan-2-yl)ethanone

2-Pentylfuran2-Methyl-1-benzofuran

1,3,5-UndecatrienePentan-1-ol

2-Ethyl-1-benzofuran3-Metylbutan-1-ol

Unknown 1363-Ethoxy-propan-1-olEthyl 2-phenylacetate

Unknown 167γ-Nonalactone

Unknown 452-Ethoxyetyl acetate

(Z)-Hex-3-enyl butanoate(Z)-Hex-3-enyl 2-methylbutanoate

EstragolUnknown 178Unknown 123Unknown 138Unknown 154Unknown 172

Tridecan-2-oneUnknown 161Unknown 179

(2E,4Z)-deca-2,4-dienoateUnknown 168(E,E)-FarnesalUnknown 169(Z,E)-Farnesol

PropionoinUnknown 174

(Z,E)-α-Farnesene(E,E)-α-Farnesene

Dihydrofarnesol(Z,E)-Farnesal

3-Pentyl-2H-furan-5-oneUnknown 176Unknown 180Nonan-4-one

γ-Undecalactonetrans-Nerolidol(E,E)-FarnesolUnknown 158Unknown 160Unknown 165Unknown 142Unknown 151Unknown 162

EthanolEthyl hexanoateEthyl octanoateEthyl decanoate

Heptan-1-olEthyl heptanoate

3-Methylbutyl hexanoateEthyl 9-decenoate

MF MP MS ML MH CN SCMA

II

III

IV

I

V

VI


https://doi.org/10.1101/721845

Unknown 132Unknown 147

2-Phenylethyl acetate2- Methylbutyl acetate3-Methylbutyl acetate

1,1-DiethoxyethaneEthyl 2-methylpropanoate

Ethyl acetate2-Methylpropyl acetate

1-(1-Ethoxyethoxy)butaneAmyl alcohol

3-Methylsulfanylpropan-1-olIsobutanol

2-Phenylethanol3-Methylbutyl propanoate

3-Methylpentan-1-olSulcatol

β-CitronellolUnknown 118Butyl acetate

Butyl butanoateNonan-2-ol

iso-HexanolUnknown 137

(3-Methylphenyl)methanolGeraniol

IsoprenolLinalool

SulcatoneEthyl propanoate

Ethyl 3-methylbutanoateEthyl 3-methylbenzoate

Propyl acetatePentyl acetate

DecanalOctanal

NonanalUnknown 98

2-Ethylhexan-1-olButyl hexanoate

(3E)-4,8-dimethylnona-1,3,7-trieneHexyl 2-methyl butanoate

Unknown 143Heptan-2-oneNonan-2-oneUnknown 70Unknown 85Unknown 87

2-Pentylthiophene2-Methylbut-2-en-1-ol

2-Methylpentan-1-olGeranyl acetone

Octan-3-oneHeptane-2,3-dione

Heptan-3-oneFuscumol

CyclohexanoneUndecan-2-one

Ethyl (E)-2-methylbut-2-enoateEthyl furan-3-carboxylateEthyl 3-ethoxypropanoate

Ethyl 2-furanoateMethanol

AcetoinEthyl benzoate

IndoleHexyl acetate

2-Methylthiolan-3-oneIsobutanoic acid

3-Methyl butanoic acid2-Ethylbutan-1-ol

Heptan-4-oneUnknown 109

Methyl palmitateMethyl elaidate

Heptan-4-olHeptan-2-olOctan-1-ol

Unknown 1592-Methylbutyl 2-methylbutanoate

α-Terpineol(Z)-Hex-3-enyl acetate

Ethyl butanoateEthyl 2-methylbutanoate

b-Myrcene1,2-Xylene

2-Methylpropyl 2-methylpropanoateUnknown 100

Ethyl hex-2-enoate2-Methylbutanoyl 2-methylbutanoate

BenzonitrileIsogeraniolCamphene2-Hexanol

2-Metylpropyl butanoate3-Methylbutyl butanoate

Hexan-3-olHexyl butanoate

VII

VIII

IX

X

XI

XII

XIII

XIV


https://doi.org/10.1101/721845


https://doi.org/10.1101/721845

0 0.2 0.4 0.6-0.2-0.4-0.6-0.8

M. andauensis

S. cerevisiae

M. pulcherrima

M. fructicola

M. saccharicola

M. hawaiiensis

M. lopburiensis

C. nemorosus

Avoidance (RI<0) Feeding (RI>0)

**

**

**

**

**

*

Component 1 (Q2 = 0.43)

Co

mp

onent

2 (Q

2 =

0.3

8)

FeedingAvoidance

n.s.

n.s.

n.s.

-6

-4

-2

0

2

4

6

-8 -6 -4 -2 0 2 4 6 8

A B


https://doi.org/10.1101/721845

-0.6 -0.4 -0.2 0 0.2 0.4 0.6

C.

nem

oro

su

s v

s.

oth

er

sp

ecie

s e

xcep

t M

. an

du

aen

sis Geranyl acetone

Unique

M. andauensis

Unique

C. nemorosus

Shared +/+

Shared -/-

Cyclohexanone

2-Ethyl-1-benzofuran

1,3,5-Undecatriene

Nonan-2-ol

Methanol

2-Phenyl ethanal

M. andauensis vs. other species except C. nemorosus

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

Unknown 159

Unknown 132

2-Methylbutyl 2-methyl-

butanoate

2-Phenylethyl acetate

3-Methylbutyl propanoate

3-Methylpentan-1-ol

Isobutanoic

acid

Unknown 147Heptan-4-ol

Camphene

3-Methylbutyl acetate

2-Methylbutyl acetate

Ethanol

3-Methyl butanoic acid


https://doi.org/10.1101/721845

TABLE S1 Volatile compounds identified by GC-MS from the headspace of eight yeasts, Cryptococcus nemorosus, M. andauensis, M. fructicola, M. hawaiiensis, M. lopburiensis, M. pulcherrima, M. saccharicola and Saccharomyces cere-visiae. Compounds marked with a bullet are not listed in yeast databases, two bullets for compounds not known from databases of yeast, bacterial or fungal metabolites. Compound nomenclature follows IUPAC, according to PubChem. CAS and CID number are shown, and Kovats indices on a DB-Wax column. Letters R and W denote compounds listed in yeast metabolome databases by Ramirez-Gaona et al. (2017)a and Weldegergis et al. (2011)b, followed by the number of bacteria and fungi, respectively, producing these compounds according to Lemfack et al. (2018)c.

Compound Synonym CAS number

PubChem CID

Kovats DB-Wax

Database recordsa,b,c

Ethyl acetate 141-78-6 8857 800 R,W,10,30

• Methanol 67-56-1 887 812 12,1 Ethanol 64-17-5 702 884 R,18,42 1,1-Diethoxyethane 105-57-7 7765 890 R,W,0,0 Methyl 2-methylpropanoate 547-63-7 11039 920 R,12,4 Ethyl propanoate 105-37-3 7749 954 R,W,1,13 Ethyl 2-methylpropanoate 97-62-1 7342 963 W,3,2 Propyl acetate 109-60-4 7997 971 R,W,1,2 Methyl butanoate 623-42-7 12180 982 R,W,14,8 1-(1-Ethoxyethoxy)butane 57006-87-8 552119 997 W,0,0 • (±)-Methyl 2-methylbutanoate 868-57-5 13357 1007 13,9

2-Methylpropyl acetate 110-19-0 8038 1010 R,W,3,2

• Methyl 3-methylbutanoate 556-24-1 11160 1016 28,2 Ethyl butanoate 105-54-4 7762 1034 R,W,10,8 (±)-Ethyl 2-methylbutanoate 7452-79-1 24020 1051 R,W,16,13 Ethyl 3-methylbutanoate 108-64-5 7945 1067 R,W,5,6 2,2-Dimethyl-3-methylidenebicyclo[2.2.1]heptane Camphene 79-92-5 6616 1067 R,1,18 Butyl acetate 123-86-4 31272 1070 R,W,9,3 2-Methyl-propan-1-ol Isobutanol 78-83-1 6560 1078 R,47,52 • 2-Methylpropyl 2-methylpropanoate 97-85-8 7351 1090 0,3 • (±)-Methyl 2-methylpentanoate 2177-77-7 519890 1096 2,0 (±)-2-Methylbutyl acetate 624-41-9 12209 1113 R,W,2,2 3-Methylbutyl acetate 123-92-2 31276 1121 R,W,12,7 • Heptan-4-one 123-19-3 31246 1125 8,1 •• (±)-Methyl 3-methylpentanoate 2177-78-8 519891 1129 0,0 • Heptane-2,3-dione 96-04-8 60983 1146 1,0 Heptan-3-one 106-35-4 7802 1153 W,1,0 2-Metylpropyl butanoate 539-90-2 10885 1158 R,0,0 7-Methyl-3-methylideneocta-1,6-diene β-Myrcene 123-35-3 31253 1162 R,W,2,9 Pentyl acetate 628-63-7 12348 1171 R,W,0,1 Heptan-2-one 110-43-0 8051 1182 R,W,32,21 Methyl hexanoate 106-70-7 7824 1186 R,W,2,0 1,2-Xylene 95-47-6 7237 1186 R,4,3 3-Methylbutyl propanoate 105-68-0 7772 1188 R,2,1

•• (±)-Hexan-3-ol 623-37-0 12178 1192 0,0 (±)-2-Methylbutan-1-ol Amyl alcohol 137-32-6 8723 1202 R,W,40,52 3-Metylbutan-1-ol 123-51-3 31260 1204 R,W,128,67 (±)-Hexan-2-ol 626-93-7 12297 1216 R,W,0,7 Butyl butanoate 109-21-7 7983 1218 R,3,0 2-Pentylfuran 3777-69-3 19602 1230 R,W,3,63 Ethyl hexanoate 123-66-0 31265 1234 R,W,10,12 • Ethyl (E)-2-methylbut-2-enoate 5837-78-5 5281163 1237 0,2 • 3-Methylbut-3-en-1-ol Isoprenol 763-32-6 12988 1246 23,2 Pentan-1-ol 71-41-0 6276 1246 R,4,45


https://doi.org/10.1101/721845

Unknown 45

1251 - Octan-3-one 106-68-3 246728 1255 R,8,51 • 3-Methylbutyl butanoate 106-27-4 7795 1266 2,1 Hexyl acetate 142-92-7 8908 1271 R,W,1,0 • Heptan-4-ol 589-55-9 11513 1279 1,0 • (±)-2-Methylbutyl 2-methylbutanoate 2445-78-5 17129 1281 0,3 3-Hydroxybutan-2-one Acetoin 513-86-0 179 1285 R,69,14

•• 2-Ethoxyetyl acetate 111-15-9 8095 1289 0,0 Octanal 124-13-0 454 1289 R,W,10,3

•• Methyl (E)-hex-2-enoate 2396-77-2 5364409 1291 0,0 • (±)-2-Methyl pentan-1-ol 105-30-6 7745 1295 0,1 • Cyclohexanone 108-94-1 7967 1300 3,0 2-Ethylbutan-1-ol 97-95-0 7358 1304 W,0,0

•• (3E)-4,8-dimethylnona-1,3,7-triene 19945-61-0 6427110 1306 0,0 4-Methylpentan-1-ol iso-Hexanol 626-89-1 12296 1310 R,W,0,1 Heptan-2-ol 543-49-7 10976 1315 R,W,7,7 (Z)-Hex-3-enyl acetate 3681-71-8 5363388 1316 R,0,0 • 2-Methylbut-2-en-1-ol 4675-87-0 20799 1317 1,0

(±)-3-Methylpentan-1-ol 589-35-5 11508 1324 R,W,0,2

• Nonan-4-one 4485-09-0 78236 1328 0,2 • Ethyl 3-ethoxypropanoate 763-69-9 12989 1330 0,1 Ethyl heptanoate 106-30-9 7797 1333 R,W,0,0 6-Methylhept-5-en-2-one Sulcatone 110-93-0 9862 1338 R,W,24,30 Ethyl hex-2-enoate 1552-67-6 5364778 1346 R,0,1 1-Hexanol 111-27-3 8103 1349 R,W,34,53 Unknown 70

1361 -

Unknown 71

1367 - 3-Ethoxy-propan-1-ol 111-35-3 8109 1376 R,0,0 (Z)-Hex-3-en-1-ol 928-96-1 5281167 1382 R,W,0,6 Methyl octanoate 111-11-5 8091 1389 R,W,0,0 Nonan-2-one 821-55-6 13187 1391 R,W,87,18 Nonanal 124-19-6 31289 1395 R,22,37

•• (±)-Methyl 2-hydroxy-3-methylbutanoate 17417-00-4 552631 1399 0,0 •• 1,3,5-Undecatriene 16356-11-9 5367412 1406 0,0 • (E)-Oct-3-en-2-one 1669-44-9 5363229 1411 0,2 • Butyl hexanoate 626-82-4 12294 1414 1,0

(±)-4-Hydroxyhexan-3-one Propionoin 4984-85-4 95609 1415 R,1,1

•• Hexyl butanoate 2639-63-6 17525 1416 0,0 •• (±)-Hexyl 2-methyl butanoate 10032-15-2 24838 1429 0,0 Unknown 84

1431 -

Unknown 85

1432 - Ethyl octanoate 106-32-1 7799 1436 R,W,8,2 Unknown 87

1440 -

•• Furan-2-carbohydrazide 3326-71-4 18731 1440 0,0 (±)-Oct-1-en-3-ol 3391-86-4 18827 1444 R,W,5,105 Unknown 90

1445 -

** 2-Methylbutanoyl 2-methylbutanoate 1519-23-9 102642 1451 0,0 Heptan-1-ol 111-70-6 8129 1452 R,W,37,39 (±)-6-Methylhept-5-en-2-ol Sulcatol 1569-60-4 20745 1458 W,2,0 3-Methylbutyl hexanoate 2198-61-0 16617 1460 R,W,0,0 (Z)-Hex-3-enyl butanoate 16491-36-4 5352438 1461 R,0,0 Unknown 96

1462 -

2-Pentylthiophene 4861-58-9 20995 1465 R,1,0 Unknown 98

1473 -

•• (Z)-Hex-3-enyl (±)-2-methylbutanoate 53398-85-9 5365069 1474 0,0

Unknown 100

1477 -

•• Methyl (±)-3-hydroxybutanoate 1487-49-6 15146 1482 0,0


https://doi.org/10.1101/721845

Ethyl furan-3-carboxylate 614-98-2 69201 1483 R,0,0 (±)-2-Ethylhexan-1-ol 104-76-7 7720 1485 R,W,13,39

•• Methyl (±)-2-hydroxy-3-methylpentanoate 41654-19-7 521064 1495 0,0 Decanal 112-31-2 8175 1501 R,W,25,39 1-(Furan-2-yl)ethanone 1192-62-7 14505 1508 R,W,18,1 Nonan-2-ol 628-99-9 12367 1514 R,W,1,0 Methyl 3-methylsulfanylpropanoate 13532-18-8 61641 1528 R,0,0 Unknown 109

1530 -

Benzaldehyde 100-52-7 240 1533 R,W,61,48 2-Methylthiolan-3-one 13679-85-1 61664 1540 R,W,2,0 (±)-3,7-Dimethylocta-1,6-dien-3-ol Linalool 78-70-6 6549 1542 R,W,5,11 Octan-1-ol 111-87-5 957 1555 R,W,18,17 2-Methylpropanoic acid Isobutanoic acid 79-31-2 6590 1560 R,30,7

Ethyl 3-methylsulfanylpropanoate Ethyl 3-methylthio-propanoate 13327-56-5 61592 1572 R,W,0,0

Methyl furan-2-carboxylate Methyl 2-furoate 611-13-2 11902 1580 W,5,5 •• 4-Ethylbenzene-1,3-diol 2896-60-8 17927 1584 0,0 Unknown 118

1588 -

Undecan-2-one 112-12-9 8163 1603 R,108,14

•• 2-Methyl-1-benzofuran 4265-25-2 20263 1607 0,0 • Benzonitrile 100-47-0 7505 1619 4,0 Ethyl furan-2-carboxylate Ethyl 2-furanoate 614-99-3 11980 1624 W,0,0 Unknown 123

1628 -

Methyl benzoate 93-58-3 7150 1634 W,6,4 Ethyl decanoate 110-38-3 8048 1641 R,W,3,1 2-Phenylacetaldehyde 2-Phenyl ethanal 122-78-1 998 1652 R,W,18,13 3-Methyl butanoic acid 503-74-2 10430 1666 R,94,8 Ethyl benzoate 93-89-0 7165 1678 R,W,0,2 • 1-Methoxy-4-prop-2-enylbenzene Estragole 140-67-0 8815 1679 0,2 •• 2-Ethyl-1-benzofuran 3131-63-3 76582 1692 0,0 Ethyl dec-9-enoate Ethyl 9-decenoate 67233-91-4 522255 1692 R,W,0,0 Unknown 132

1697 -

(±)-2-(4-methylcyclohex-3-en-1-yl)propan-2-ol α-Terpineol 98-55-5 17100 1704 R,W,15,5 3-Methylsulfanylpropan-1-ol 505-10-2 10448 1722 R,W,27,3 (3Z,6E)-3,7,11-Trimethyldodeca-1,3,6,10-tetraene (Z,E)-α-Farnesene 26560-14-5 5362889 1726 W,0,4 Unknown 136

1731 -

Unknown 137

1738 - Unknown 138

1741 -

(3E,6E)-3,7,11-Trimethyldodeca-1,3,6,10-tetraene (E,E)-α-Farnesene 502-61-4 5281516 1750 R,0,4 (±)-3,7-Dimethyloct-6-en-1-ol β-Citronellol 106-22-9 8842 1763 R,W,0,3 Methyl 2-phenylacetate 101-41-7 7559 1768 R,2,4 Unknown 142: sesquiterpene

1771 -

Unknown 143: sesquiterpene

1784 - 7-Methyl-3-methylideneoct-6-en-1-ol γ-Isogeraniol 13066-51-8 518689 1786 W,0,0 Ethyl 2-phenylacetate 101-97-3 7590 1793 W,0,0 (2Z)-3,7-Dimethylocta-2,6-dien-1-ol Nerol 106-25-2 643820 1801 R,W,0,0 Unknown 147

1804 -

•• Ethyl 3-methylbenzoate 120-33-2 67117 1806 0,0

(3Z)-3,7-Dimethylocta-3,6-dien-1-ol Isogeraniol 5944-20-7 6536347 1810 W,0,0

• Tridecan-2-one 593-08-8 11622 1815 54,1 Unknown 151: sesquiterpene

1822 -

2-Phenylethyl acetate 103-45-7 7654 1826 R,W,5 •• 3-Pentyl-2H-furan-5-one 62527-72-4 12320141 1828 0,0 Unknown 154

1835 -

(2E)-3,7-Dimethylocta-2,6-dien-1-ol Geraniol 106-24-1 637566 1845 R,5,1 •• Ethyl (2E,4Z)-deca-2,4-dienoate Pear ester 3025-30-7 5281162 1847 0,0 (5E)-6,10-dimethylundeca-5,9-dien-2-one Geranyl acetone 689-67-8 1549778 1860 R,14,6


https://doi.org/10.1101/721845

Unknown 158

1878 - Unknown 159

1883 -

Unknown 160

1888 - Unknown 161

1901 -

Unknown 162

1901 - 2-Phenylethanol 60-12-8 6054 1921 R,W,134,45

•• (5E)-6,10-Dimethylundeca-5,9-dien-2-ol Fuscumol 53837-34-6 5370125 1953 0,0

Unknown 165

1965 -

•• (3-Methylphenyl)methanol 587-03-1 11476 1969 0,0 Unknown 167

1972 -

Unknown 168

1979 - Unknown 169

2001 -

Unknown 170

2032 - (±)-(6E)-3,7,11-Trimethyldodeca-1,6,10-trien-3-ol trans-Nerolidol 7212-44-4 5284507 2037 R,W,1,8 Unknown 172

2043 -

5-Pentyloxolan-2-one γ-Nonalactone 104-61-0 7710 2049 R,W,5,0 Unknown 174

2056 -

Unknown 175

2065 - Unknown 176

2079 -

Unknown 177

2087 - Unknown 178

2089 -

Unknown 179

2097 - Unknown 180

2135 -

5-Hexyloxolan-2-one γ−Decalactone 706-14-9 12813 2166 R,W,5,0 Methyl hexadecanoate Methyl palmitate 112-39-0 8181 2223 1,1

•• (2Z,6E)-3,7,11-Trimethyldodeca-2,6,10-trienal (Z,E)-Farnesal 4380-32-9 5365890 2235 0,0

Ethyl hexadecanoate Ethyl palmitate 628-97-7 12366 2266 R,W,0,1

• (±)-3,7,11-Trimethyldodeca-6,10-dienol Dihydrofarnesol 37519-97-4 5280341 2278 0,1 •• (2E,6E)-3,7,11-Trimethyl-2,6,10-dodecatrienal (E,E)-Farnesal 19317-11-4 5280598 2292 0,0

5-Heptyloxolan-2-one γ-Undecalactone 104-67-6 7714 2298 R,4,0

Ethyl (E)-hexadec-9-enoate Ethyl palmitoleate 54546-22-4 5364759 2302 R,0,0 •• (2Z,6E)-3,7,11-Trimethyl-2,6,10-dodecatrien-1-ol (Z,E)-Farnesol 3790-71-4 1549108 2342 0,0

(2E,6E)-3,7,11-Trimethyl-2,6,10-dodecatrien-1-ol (E,E)-Farnesol 106-28-5 445070 2396 R,W,2,1

•• Methyl (E)-octadec-9-enoate Methyl elaidate 1937-62-8 5280590 2544 0,0

1H-Indole Indole 120-72-9 798 2560 R,W,36,3

aRamirez-Gaona M, Marcu A, Pon A, Guo AC, Sajed T, Wishart NA, Karu N, Feunang YD, Arndt D and Wishart DS. 2017. YMDB 2.0: a significantly expanded version of the yeast metabolome database. Nucleic Acids Res 45(D1):D440-D445. bWeldegergis BT, Crouch AM, Górecki T, De Villiers A. 2011. Solid phase extraction in combination with compre-hensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry for the detailed investigation of volatiles in South African red wines. Analytica Chimica Acta 701:98-111. cLemfack MC, Gohlke BO, Toguem SMT, Preissner S, Piechulla B, Preissner R. 2018. mVOC 2.0: a database of micro-bial volatiles. Nucleic Acids Res 46(D1):D1261-D1265.


https://doi.org/10.1101/721845

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