Candida albicans

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Real-time detection of common microbial volatile organic compounds from medically important fungi by Selected Ion Flow Tube-Mass Spectrometry (SIFT-MS).

TARGETED METABOLITES OF Candida albicans THROUGH COMPREHENSIVE TWO DIMENSIONAL GAS CHROMATOGRAPHY Catarina Ferreiraa,*, Carina P. Costaa,*, Adelaide Almeidaa, Sílvia M. Rochab aDepartamento de Biologia & CESAM, Universidade de Aveiro, 3810-193 Aveiro, Portugal bDepartamento de Química & QOPNA, Universidade de Aveiro, 3810-193 Aveiro, Portugal *These authors contributed equally to this work

Introduction

Methodology

Candida albicans is the major fungal pathogen causing opportunist infections, which manifest particularly in immunocompromised individuals. Invasive fungal infections are associated with high mortality rate due to a late diagnosis and subsequent delay in early antifungal therapy. Laboratory diagnosis of fungal infections remains based on conventional methods, however, they fail to provide as quick results as desired during life-treatment solutions, since the average time required for accurate identification by these culture-based methods is ranged from days to weeks [1,2].

1. Fungi growth

2. Sample preparation and metabolites extraction

CFU (colony forming unit)determination

Microbial metabolomics has been breaking new ground as a very useful tool in several areas, including those related to microbial diagnosis. Microorganisms produce several volatile metabolites that can be used for microbial detection through chemical fingerprints of each species [3]. A set of metabolites, 3-methyl-butanol, 1-dodecanol, 2-phenylethanol, nerolidol, and farnesol, have been reported as C. albicans quorum sensing molecules [4-6]. In order to go further on the establishment of volatile metabolites patterns that can be used for fungal detection, this research aims to develop a platform for C. albicans detection management, using a methodology based on headspace-solid phase microextraction combined with GC×GC coupled to mass spectrometry with a high resolution time-of-flight analyzer (HS-SPME/GC×GC-ToFMS). C. albicans was studied upon different growth conditions: i) two temperatures were assayed (25 and 37 °C - 25 °C is the temperature commonly used for laboratory assays [7], also fungi are able to grow at 37 °C during a host infection), ii) four growth times (6, 12, 24 and 48 hours – 24 to 72 hours are applied in the methods currently performed in clinical laboratories, however this study aims to reduce the growth time).

He

Candida albicans – growth conditions Temperature: 25 and 37 °C

HS-SPME

GC×GC–ToFMS Pegasus 4D

Incubation time: 6, 12, 24 and 48 hours Culture medium: Yeast Glucose Chloramphenicol (YGC) without agar (liquid medium)

4. Data processing

SPME conditions: • 20 mL sample volume (60 mL glass vial) • 30/50 μm DVB/CAR/PDMS (1 cm) • 30 min, at 50 °C

Heatmap

Metabolite

CAS number

Formula

RICalc

PC1

PC1 PC2

PC2

PC1

PC2

PC1

For both temperatures, alcohols and aldehydes were mainly produced for the short growth times, while, esters and sesquiterpenols were produced for longer times.

4. Statistical analysis applied to the data set comprising 15 metabolites PCA scatter score plot

2. Set of 15 targeted metabolites (s)

PC2

The heatmap comprises the data obtained upon different growth conditions: the temperature (25 and 37 °C) and the incubation period (6, 12, 24 and 48 hours). Each variable area was normalized by the maximum of each metabolite for all samples (with GC peak previously normalized by CFU mL-1).

The targeted metabolites of C. albicans are highlighted in the contour plot (see peak assignment in the following table).

b

PC1

3. Heatmap of the 15 selected metabolites identified from C. albicans cultures

From hundreds of detected metabolites, a set of 15 metabolites were selected: metabolites detected in all the growth conditions tested, including those known as C. albicans quorum sensing molecules [4-6].

2t a (s) R

PC2

PCA

The GC×GC-ToFMS total ion chromatogram contour plot represents C. albicans volatile exometabolome.

1t a R

PC1

PC1

1. GC×GC-ToFMS total ion chromatogram contour plot released by C. albicans cultures

Peak Number

PC2

PC2

Loadings weight

• agitation (350 rpm)

Results and Discussion

Selection of a set of 15 metabolites

3. GC×GC analysis

Loadings plot

RILitc GC×GC

GC-MS

Alcohols Aliphatic 1

85

0.680

1-Propanol

71-23-8

C3H8O

580

-

574

2

100

0.770

2-Methyl-1-propanol

78-83-1

C4H10O

612

615

-

3

145

1.080

2/3-Methyl-1-butanol

137-32-6/123-51-3

C5H12O

718/708

743/706

-

4

775

0.930

1-Dodecanol

112-53-8

C12H26O

1476

1470

-

60-12-8

C8H10O

1126

1132

-

Aromatic 5

480

2.990

2-Phenylethanol Aldehydes

6

70

0.350

Acetaldehyde

75-07-0

C2H4O

548

500

-

7

110

0.660

2-Butenal

4170-30-3

C4H6O

633

-

657

Esters 8

95

0.440

Ethyl acetate

141-78-6

C4H8O2

601

613

-

9

135

0.480

Ethyl propanoate

105-37-3

C5H10O2

685

684

-

10

195

0.510

Ethyl butanoate

105-54-4

C6H12O2

806

807

-

11

255

0.560

Isoamyl acetate

123-92-2

C7H14O2

877

-

876

67-64-1

C3H6O

559

-

503

Ketones 12

75

0.390

2-Propanone Sesquiterpenols

13

850

0.900

Nerolidol

142-50-7

C15H26O

1566

1573

-

14

990

1.250

Farnesol

106-28-5

C15H26O

1731

-

1730

a

Retention times for first (1tR) and second (2tR) dimensions in seconds. b RI Calc: Retention Index obtained through the modulated chromatogram. c RI : Retention Index reported in the literature for Equity-5 column or equivalents. Lit

Concluding remarks

Samples were dispersed through PC1 according to the growth time, being those from short times located at PC1 negative and the samples from longer ones at PC1 positive. Samples obtained at 6 hours (25 and 37°C) and 12 hours (25°C) of growth were characterized by 2/3-methyl-1-butanol, 1-dodecanol, acetaldehyde, and 2-butenal, mainly associated with fatty acids metabolism, otherwise, the others metabolites, related to leucine and valine metabolismo, and mevalonate pathway [8-10], characterize the samples obtained from higher growth times.

 The headspace content of C. albicans was performed upon different growth conditions, using a

 The exometabolome revealed itself complex, comprising several hundreds of metabolites, from

methodology based on solid phase microextraction combined with advanced multidimensional gas

those 15 metabolites present in all conditions tested were selected as a potential biomarker

chromatography. This study goes a step further on exploring the potentialities of GC×GC as a high

pattern for C. albicans detection, which are related to amino acids metabolism, biosynthesis of

throughput tool towards C. albicans future detection based on a molecular biomarkers pattern.

fatty acids and mevalonate pathways, as well as quorum sensing molecules.

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