SciELO - Scientific Electronic Library Online

vol.27 número1Aplicaciones de citometría de flujo en fitomejoramientoSecuenciación de moléculas individuales de ácidos nucleicos en tiempo real (SMRT) para caracterizar transcriptomas e isoformas de ARNm índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados




  • No hay articulos citadosCitado por SciELO

Links relacionados


Revista Peruana de Biología

versión On-line ISSN 1727-9933

Rev. peru biol. vol.27 no.1 Lima ene./mar 2020 

Artículo de congreso

A simple and accurate method for specific quantification of biomass in mixed cultures of filamentous fungi by quantitative PCR

Un método simple y preciso para la cuantificación específica de biomasa en cultivos mixtos de hongos filamentosos por PCR cuantitativa

Alonso Reyes-Calderón1

Katherine Ruth Garcia-Luquillas1

Yvette Ludeña1

Maria Lucila Hernández-Macedo1

Gretty K. Villena1

Ilanit Samolski1  *

1Laboratorio de Micología y Biotecnología (LMB), Facultad de Ciencias, Universidad Nacional Agraria La Molina, Lima 12, Perú. Tel: +511 6147800 - 463


Production of lignocellulolytic enzymes by filamentous fungi have a great potential at industrial level due to their widespread applications. Mixed fungal cultures and particularly mixed fungal biofilms constitute a promising fermentation system for an enhanced enzyme production. However, it has not been addressed how much of this enhancement depends on the mixed biomass proportion. In this sense, the aim of this study was to develop a method to specifically and accurately quantify mixed fungal biomass. For this purpose, mixed biofilm cultures composed of Aspergillus niger and Trichoderma reesei, two filamentous fungi used industrially for cellulase production, were collected from 48 to 120 h of growth; mycelia were pulverized, and DNA was extracted for qPCR assays with specific primers for each fungus. Primers were designed from non-conserved regions of sequences of actin and β-tubulin genes of both A. niger and T. reesei. Specificity of these primers was tested in silico and experimentally. A statistically significant correlation was obtained between qPCR-calculated biomass and dry weight biomass data. By this method, it was possible to detect changes on mycelia proportions in biofilms over time, suggesting a competitive interaction between these two fungi. In conclusion, this method allows a specific and accurate quantification of mixed fungal biomass and could be also applied to different mixed culture systems for studying microbial interactions.

Keywords: Lignocellulolytic enzymes; Aspergillus niger; Trichoderma reesei; mixed cultures; biofilms; coculture; qPCR; specific quantification; microbial interactions


La producción de enzimas lignocelulolíticas por hongos filamentosos tiene un gran potencial a nivel industrial debido a sus diversas aplicaciones. Los cultivos fúngicos mixtos y particularmente las biopelículas fúngicas mixtas constituyen un sistema de fermentación prometedor para una mayor producción enzimática. Sin embargo, no se ha abordado cuánto de esta mejora depende de la proporción de biomasa mixta. En este sentido, el objetivo de este estudio fue desarrollar un método para cuantificar de forma específica y precisa la biomasa fúngica mixta. Para este propósito, se recolectaron cultivos mixtos de biopelículas de 48 a 120 h de crecimiento compuestos por Aspergillus niger y Trichoderma reesei, dos hongos filamentosos utilizados industrialmente para la producción de celulasas; el micelio se pulverizó y el ADN se extrajo para ensayos de qPCR con cebadores específicos para cada hongo. Los cebadores se diseñaron a partir de regiones no conservadas de las secuencias de los genes de actina y β-tubulina de A. niger y T. reesei. La especificidad de estos cebadores se probó in silico y experimentalmente. Se obtuvo una correlación estadísticamente significativa entre la biomasa calculada mediante qPCR y los datos de biomasa en peso seco. Mediante este método, fue posible detectar cambios en las proporciones de los micelios en las biopelículas a lo largo del tiempo, lo que sugiere una interacción competitiva entre estos dos hongos. En conclusión, este método permite una cuantificación específica y precisa de la biomasa fúngica mixta y también podría aplicarse a diferentes sistemas de cultivo mixto para estudiar interacciones microbianas.

Palabras clave: Enzimas lignocelulolíticas; Aspergillus niger; Trichoderma reesei; cultivos mixtos; biopelículas; cocultivo; qPCR; cuantificación específica; interacciones microbianas


Industrial enzyme production has a wide application in biotechnology, because of the high market value of this proteins and the potential use of renewable and low-cost raw materials, such as cellulose and lignocellulose (Kirk et al. 2002, Kuhad et al. 2011, Guerriero et al. 2015). Lignocellulose is the major component of plant biomass, comprising around half of the matter produced by photosynthesis and representing the most abundant renewable organic resource in soil (Sánchez 2009). However, obtaining sugars from lignocellulosic biomass for fermentation is still an expensive process, mostly due to low enzyme yields of producing microorganisms (Galbe & Zacchi 2002) and chemical complexity and variability of this substrate (Karimi & Taherzadeh 2016). Thus, optimal use of lignocellulose depends on the selection of microorganisms that exhibit a high lignocellulase enzymatic yield, as well as culture systems that guarantee and promote this production.

Previous studies have demonstrated that growth in a mixed biofilm system formed by filamentous fungi Aspergillus niger and Trichoderma reesei, leads to a total cellulase yield increase of 50-70% with respect to single biofilm cultures (Villena 2002, Gutiérrez-Correa & Villena 2012). Although mixed cultures constitute a promising fermentation system, it has not been yet addressed how much of this enzymatic synergy depends on a certain proportion of fungal mixed biomass and what are the effects of growth rate and culture time on this proportion. In order to assess the influence of fungi proportion on the mixed biofilm system productivity, it is essential to develop a method to accurately determine biomass of each species in mixed cultures.

When direct quantification of biomass is not possible (e. g., sample scarcity, irreversible biomass-substrate binding), an indirect approach might be a more feasible manner to collect biomass data. Several methods for indirect biomass quantification have been developed, namely, microscopic techniques such as spore counting or hyphal thickness and length measurement (Schnürer 1993, Balser et al. 2005); cell membrane and wall components quantification like ergosterol (Gessner et al. 1991, Nylund & Wallander 1992, Lau et al. 2006), phospholipid fatty acids (Olsson et al. 1995) and glucosamine (Matcham et al. 1985); and additionally inner-cell components such as total protein (Abd-Aziz et al. 2008) and DNA (Zhao et al. 2013, Liu et al. 2017). Methods based on DNA quantification receive increasing attention for their ability not only to estimate microbial biomass content but also to provide species composition data (Baldrian et al. 2013). In this sense, the aim of this work was to develop a method that allows an accurate quantification of A. niger ATCC 10864 and T. reesei QM6a biomass in a mixed biofilm system by means of the specific quantification of the genomic DNA (gDNA) of each fungus by quantitative PCR (qPCR).

Material and Methods

Fungal growth conditions.- Aspergillus niger ATCC 10864 and Trichoderma reesei QM6a were kindly donated by the Agricultural Research Service (ARS) Collection of the United States Department of Agriculture (USDA). The strains were maintained on potato-dextrose agar (PDA) slants at 28 °C in the dark until complete spore germination (∼5 days). Spores were collected with 0.1% Tween 80 solution, counted with a hemocytometer and diluted in sterile distilled water.

Mixed biofilm formation.- Spore suspensions (1 x 106 spores/mL) were used as inoculum for biofilm formation in a proportion of 1.5% (v/v) for each fungus (Villena 2002). Briefly, 250 mL flasks containing a polyester fiber square (9.61 cm2) in 70 mL of sterile distilled water were inoculated with 1.05 mL of T. reesei spore suspension and incubated at 28 °C and 175 rpm for 2 h in order to allow spore adhesion. After this contact period, cloths were washed three times with sterile distilled water for 15 min at 175 rpm in order to remove non-adhered spores and transferred to new 250 mL flasks containing 70 mL of sterile distilled water. Then, flasks were inoculated with 1.05 mL of A. niger spore suspension and incubated for 30 min under the same conditions than T. reesei spores. Finally, co-inoculated cloths were washed as described previously and transferred to new flasks containing 70 mL of the culture medium for biofilm formation at 28 °C and 120 rpm for 120 h (Villena & Gutiérrez-Correa 2006). At each time point, mixed biofilms were recovered by filtration, washed with sterile distilled water and dried under vacuum at 45 °C for 2 h using a Concentrator Plus (Eppendorf, DE). Dry biofilms were kept at -80 °C until gDNA extraction.

gDNA extraction.- Freeze-dried biofilms were ground in liquid nitrogen using a mortar and pestle. Subsequently, 10 mg of pulverized biomass was used for gDNA extraction according to Cenis (1992) with some modifications. Briefly, biomass was disrupted in microtubes containing 500 μL of lysis buffer and 200 mg of 0.5 mm glass beads by vigorously vortexing for 10 min. Disrupted biomass was digested with 5 μg of RNAse A for 10 min at 37 °C. For protein and debris precipitation, 250 μL of 3M sodium acetate was added. gDNA was precipitated with room temperature ethanol and, after washing, pellets were resuspended in ultrapure water. gDNA integrity was confirmed by agarose gel electrophoresis and purity ratios were calculated spectrophotometrically using a Nanodrop® (Thermo Fisher Scientific, US). The amount of extracted gDNA was determined by fluorometry using the Qubit Quant-iT® dsDNA High-Sensitivity Assay Kit (Thermo Fisher Scientific, US) following the manufacturer’s instructions. For each biofilm, triplicate extractions were performed.

Diphenylamine Assay.- Biomass-gDNA correlation was tested by the diphenylamine colorimetric method according to Zhao et al. (2013).

Primer design.- Sequences of actin and β-tubulin genes of each fungal species were downloaded from the National Center for Biotechnology Information (NCBI) database. Afterwards, Clustal Omega multiple sequence alignment software was used to identify non-conserved regions between genes of both fungi. From these regions, specific primers for qPCR were designed using the PrimerQuest and OligoAnalyzer online tools (Integrated DNA Technologies, US). Primer sequences are shown in Table 1.

Specificity tests were performed in silico with Primer-BLAST and FastPCR 6.0 programs using the sequences of both genes as template. Additionally, to experimentally confirm primer specificity, a qPCR assay was performed using 500 pg of mixed gDNA, A. niger gDNA or T. reesei gDNA as template.

Table 1: Primer sequences used in this work. 

Primer code Sequence (5’-3’)

qPCR conditions.- qPCR was carried out in 96-well plates using 10 μL reaction containing 1x commercial Kapa SYBR® Fast qPCR Master Mix (2x) Universal kit, 0.2 μM of each primer and 1 μL of DNA extract (500 pg). Amplifications were performed using a CFX96TM Real-Time System thermocycler (Bio Rad, US) with standard PCR conditions of 95 °C for 3 min for initial denaturation followed by 40 cycles of 3 s at 95 °C and 20 s of alignment/extension/data collection at 60 °C. Finally, a gradient step from 65 to 95 °C with 0.5 °C increases for melting curve plotting was included. The purity of the PCR product was checked by the presence of a single melting peak. Each sample were analyzed in triplicate and the experiment was performed with both the actin and β-tubulin primers.

Standard curves.- For absolute quantification of T. reesei and A. niger gDNA in mixed biofilms, qPCR two-fold serial dilution standard curves were generated for each pair of primers (An_act1, An_tubB2, Tr_act1, Tr_tubB1) using a known proportion of mixed gDNA according to Table 2. The linear-regression equations obtained in each case (Ct versus Log DNA) allowed the calculation of the initial amount of DNA in the sample. To transform the DNA data into biomass (mg), extraction yield curves were generated using 1, 3, 5, 10 and 15 mg of mycelium from individual biofilms of A. niger and T. reesei at each time (Fig. S1).

Results and Discussion

In order to analyze mycelial proportion evolution on the biofilm over time, mixed biomass was collected from 48 to 120 h. In this regard, standard curves for qPCR quantification were generated using specific primers (Fig. 1). Mixed gDNA-based curves were used because it allows to recreate or simulate the reaction conditions of mixed gDNA samples (Daly et al. 2017), such as variable A. niger/T.reesei proportions (Table 2). Non-specific amplification (mispriming) and amplification between primers (primer-dimers) has been previously reported as a consequence of low copy number of target sequence and high primer concentration at the beginning of PCR reaction (Chou et al. 1992, Brownie et al. 1997). In fact, two melting peaks have been observed only when A. niger or T. reesei gDNA proportion was set below 0.39% (data not shown), indicating that non-specific gDNA interferes with specific primers’ amplification and this interference depends on target copy number.

Table 2: A. niger and T. reesei gDNA proportions in qPCR standard curves. 

A. niger/T. reesei gDNA (pg/pg) A. niger/T. reesei gDNA proportion (%)
640/40 94.12/5.88
320/80 80/20
160/160 50/50
80/320 20/80
40/640 5.88/94.12

Biomass data (mg) of mixed biofilms was inferred from gDNA employing extraction yield curves made for each fungal species and each time point. Relationship between gDNA and biomass was confirmed to be linear in all extraction yield curves with Pearson’s coefficient of determination (R2>0.99) and in the whole mixed culture by using the diphenylamine colorimetric method (R2=0.94).

Figure 1: qPCR standard curves of (A) actin primers An_act1 (empty squares) and Tr_act1 (filled squares) with efficiencies of 98.54% and 95.23%, respectively; and (B) β-tubulin primers An_tubB2 (empty squares) and Tr_tubB1 (filled squares) with efficiencies of 99.28% and 94.69%, respectively. (n = 3). 

Other authors have used specific biomass quantification methods. Chatterjee et al. (2016) used a quantification method based on densitometry of specific restriction fragment patterns (RFLP-like), however, it lacks a gDNA extraction and PCR normalization. Others have reported biomass content in mixed cultures in terms of gDNA proportion measured by qPCR (Arfi et al. 2013, Benoit- Gelber et al. 2017). Nevertheless, since proportions of extracted gDNA from a mixed sample do not correspond necessarily to proportions of mixed biomass, results might be biased. On the other hand, there are other authors that have established methods for quantifying specific biomass based on DNA data correction with extraction yield values (Jonkers et al. 2012, Song et al. 2014), and even correction for substrate interference on these yields (Daly et al. 2017). Here, we present a corrected method that accounts not only for inherent differences between species-specific gDNA extraction yields, but also for natural changes in mycelial composition through time, such as melanin deposition and cell wall hardening (Karakousis et al. 2006), or secretion of stress-related pigments as a result of mixed culture.

Figure 2: Mycelial abundance of A. niger and T. reesei mycelia in terms of inferred dry weight (A) and biomass percentage using actin-specific primers (B) (n = 3). 

Results of specific quantification of biomass in the mixed culture composed of A. niger and T. reesei are shown in Figure 2 in terms of biomass percentage. Quantification using β-tubulin primers was almost identical to actin primers (data not shown). We detect that mycelium proportion in biofilms changed over time: at 48 h, 62% of A. niger and 38% of T. reesei; at 72 h, 53.5% and 46.5%; at 96 h, 84.5% and 15.5% and at 120 h, 95.9% and 4.1%, respectively. In this mixed culture, it is remarkable the initial and faster T. reesei growth, in comparison to A. niger from 48 to 72 h (Figure 2A). However, in spite of its growth limitation, A. niger could overcome T. reesei, showing a highly competitive fitness that has been previously reported for this fungus (Chatterjee et al. 2016, Kolasa et al. 2014). Such behavior might be explained, rather than by growth rates, by the potential capacity of each competitor to establish antagonistic (e. g., secondary antifungal metabolites, cell wall-degrading enzymes) and defensive strategies (e. g., detoxification systems, drug resistance transporters) for displacing its “rival”, as mentioned earlier (Hiscox et al. 2018). Undoubtedly, enzymatic production in mixed cultures is dependent on this behavior, and future studies for improving lignocellulase yields should use this quantification method to assess properly individual contribution of mixed-cultured fungi to enzymatic secretion.


A specific method to indirectly quantify biomass in mixed cultures was developed. qPCR reaction conditions and species-related biomass differences that interfere with gDNA yields have been corrected by using mixed gDNA qPCR standard curves and extraction yield curves for each fungus and each time point. Relative abundance results show that the presented method for specific biomass quantification offers valuable information about mixed culture composition and biological interactions linked to lignocellulase production.

Agradecimientos / Acknowledgments:

We want to thank Dr. Marcel Gutiérrez-Correa (RIP) for the extraordinary support given during the development of this work and especially for being a great mentor


Abd-Aziz S, Hung GS, Hassan MA, Abdul Karim MI, Samat N. 2008. Indirect Method for Quantification of Cell Biomass During Solid-State Fermentation of Palm Kernel Cake Based on Protein Content. Asian J. Sci. Res. 1: 385-393. [ Links ]

Arfi Y, Levasseur A, Record E. 2013. Differential gene expression in Pycnoporus coccineus during interspecific mycelial interactions with different competitors. Appl. Environ. Microbiol. 79: 6626-6636. [ Links ]

Baldrian P, Větrovský T, Cajthaml T, DobiáŠová P, Petránková M, Šnajdr J, Eichlerová I. 2013. Estimation of fungal biomass in forest litter and soil. Fungal Ecol. 6: 1-11. [ Links ]

Balser TC, Treseder KK, Ekenler M. 2005. Using lipid analysis and hyphal length to quantify AM and saprotrophic fungal abundance along a soil chronosequence. Soil Biol. Biochem. 37: 601-604. [ Links ]

Benoit-Gelber I, Gruntjes T, Vinck A, van Veluw JG, Wösten HAB, Boeren S, Vervoort JJM, de Vries RP. 2017. Mixed colonies of Aspergillus niger and Aspergillus oryzae cooperatively degrading wheat bran. Fungal Genet. Biol. 102: 31-37. [ Links ]

Brownie J, Shawcross S, Theaker J, Whitcombe D, Ferrie R, Newton C, Little S. 1997. The elimination of primer-dimer accumulation in PCR. Nucleic Acids Res. 25: 3235-3241. [ Links ]

Cenis JL. 1992. Rapid extraction of fungal DNA for PCR amplification. Nucleic Acids Res. 20: 2380. [ Links ]

Chatterjee S, Kuang Y, Splivallo R, Chatterjee P, Karlovsky P. 2016. Interactions among filamentous fungi Aspergillus niger, Fusarium verticillioides and Clonostachys rosea: Fungal biomass, diversity of secreted metabolites and fumonisin production. BMC Microbiol. 16: 1-13. [ Links ]

Chou Q, Russell M, Birch DE, Raymond J, Bloch W. 1992. Prevention of pre-PCR mis-priming and primer dimerization improves low-copy-number amplifications. Nucleic Acids Res. 20: 1717-1723. [ Links ]

Daly P, van Munster JM, Kokolski M, Sang F, Blythe MJ, Malla S, Velasco J, de Castro Oliveira, Goldman GH, Archer DB. 2017. Transcriptomic responses of mixed cultures of ascomycete fungi to lignocellulose using dual RNA-seq reveal inter-species antagonism and limited beneficial effects on CAZyme expression. Fungal Genet. Biol. 102: 4-21. [ Links ]

Galbe M, Zacchi G. 2002. A review of the production of ethanol from softwood. Appl. Microbiol. Biotechnol. 59: 618-628. [ Links ]

Gessner MO, Bauchrowitz MA, Escautier M. 1991. Extraction and quantification of ergosterol as a measure of fungal biomass in leaf litter. Microb. Ecol. 22: 285-291. [ Links ]

Guerriero G, Hausman JF, Strauss J, Ertan H, Siddiqui KS. 2016. Lignocellulosic biomass: Biosynthesis, degradation, and industrial utilization. Eng. Life Sci. 16: 1-16. [ Links ]

Gutiérrez-correa M, Villena GK. 2012. Batch and repeated batch cellulase production by mixed cultures of Trichoderma reesei and Aspergillus niger or Aspergillus phoenicis. J. Microbiol. Biotechnol. Res. 2: 929-935. [ Links ]

Hiscox J, O’Leary J, Boddy L. 2018. Fungus wars: basidiomycete battles in wood decay. Stud. Mycol. 89: 117-124. 10.1016/j.simyco.2018.02.003. [ Links ]

Jonkers W, Estrada AER, Lee K, Breakspear A, May G, Kistler HC. 2012. Metabolome and transcriptome of the interaction between Ustilago maydis and Fusarium verticillioides in vitro. Appl. Environ. Microbiol. 78: 3656-3667. [ Links ]

Karakousis A, Tan L, Ellis D, Alexiou H, Wormald PJ. 2006. An assessment of the efficiency of fungal DNA extraction methods for maximizing the detection of medically important fungi using PCR. J. Microbiol. Methods 65: 38-48. [ Links ]

Karimi K, Taherzadeh MJ. 2016. A critical review of analytical methods in pretreatment of lignocelluloses: Composition, imaging, and crystallinity. Bioresour. Technol. 200: 1008-1018. [ Links ]

Kirk O, Borchert TV, Fuglsang CC. 2002. Industrial enzyme applications. Curr. Opin. Biotechnol. 13: 345-351. [ Links ]

Kolasa M, Ahring BK, Lübeck PS, Lübeck M. 2014. Co-cultivation of Trichoderma reesei RutC30 with three black Aspergillus strains facilitates efficient hydrolysis of pretreated wheat straw and shows promises for on-site enzyme production. Bioresour. Technol. 169: 143-148. [ Links ]

Kuhad RC, Gupta R, Singh A. 2011. Microbial cellulases and their industrial applications. Enzyme Res. 2011. [ Links ]

Lau APS, Lee AKY, Chan CK, Fang M. 2006. Ergosterol as a biomarker for the quantification of the fungal biomass in atmospheric aerosols. Atmos. Environ. 40: 249-259. [ Links ]

Liu R, Chen L, Jiang Y, Zou G, Zhou Z. 2017. A novel transcription factor specifically regulates GH11 xylanase genes in Trichoderma reesei. Biotechnol. Biofuels 10: 1-14. [ Links ]

Matcham SE, Jordan BR, Wood DA. 1985. Estimation of fungal biomass in a solid substrate by three independent methods. Appl. Microbiol. Biotechnol . 21: 108-112. [ Links ]

Nylund JE, Wallander H. 1992. Ergosterol analysis as a means of quantifying mycorrhizal biomass. Methods Microbiol. 24: 77-88. [ Links ]

Olsson PA, Bååth E, Jakobsen I, Söderström B. 1995. The use of phospholipid and neutral lipid fatty acids to estimate biomass of arbuscular mycorrhizal fungi in soil. Mycol. Res. 99: 623-629. [ Links ]

Sánchez C. 2009. Lignocellulosic residues: Biodegradation and bioconversion by fungi. Biotechnol. Adv. 27: 185-194. [ Links ]

Schnurer J. 1993. Comparison of methods for estimating the biomass of three food-borne fungi with different growth patterns. Appl. Environ. Microbiol. 59: 552-555. [ Links ]

Song Z, Vail A, Sadowsky MJ, Schilling JS. 2014. Quantitative PCR for measuring biomass of decomposer fungi in planta. Fungal Ecol. 7: 39-46. [ Links ]

Villena GK. 2002 Producción de celulasas con biopelículas mixtas de hongos filamentosos. Tesis, Magíster. Universidad Nacional Agraria La Molina. [ Links ]

Villena GK, Gutiérrez-Correa M. 2006. Production of cellulase by Aspergillus niger biofilms developed on polyester cloth. Lett. Appl. Microbiol. 43: 262-268. [ Links ]

Zhao Y, Xiang S, Dai X, Yang K. 2013. A simplified diphenylamine colorimetric method for growth quantification. Appl. Microbiol. Biotechnol . 97: 5069-5077. 10.1007/s00253-013-4893-y. [ Links ]

Fuentes de financiamiento / Funding:

This study was supported by the National Program of Innovation for Competitiveness and Productivity (Innóvate Perú); Contract N° 191-FINCYT-PNIC-BRI-2015

Aspectos éticos / legales; Ethics / legals:

This work did not require collections permits since the strains used were donated by the Agricultural Research Service (ARS) Culture Collection of the United States Department of Agriculture (USDA)


Reyes-Calderón A, Garcia-Luquillas KR, Ludeña Y, Hernández-Macedo ML, Villena GK and Samolski I. 2020. A simple and accurate method for specific quantification of biomass in mixed cultures of filamentous fungi by quantitative PCR. I Congreso Internacional de Biotecnología e innovación (ICBi), Revista peruana de biología número especial 27(1): - 000 (Marzo 2020). doi:

Supplemental material

Figure S1 gDNA extraction yield curves of A. niger mycelium collected from 48 (A), 72 (B), 96 (C), 120 (D) hours of growth and T. reesei mycelium collected from 48 (E), 72 (F), 96 (G), 120 (H) hours of growth. Slopes represent extraction yields and correlation coefficients are shown (n=3) 

*Corresponding author:

Rol de los autores / Authors Roles:

ARC, KRGL, IS: experimental design; ARC, KRGL: experiments; ARC: data analysis; ARC: writing of the manuscript; YL, MLHM, GKV, IS: supervised the experiments, reviewed and approved the manuscript

Conflicto de intereses / Competing interests:

The authors have declared that no competing interests exist

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License