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Brazilian Journal of Botany

Print version ISSN 0100-8404On-line version ISSN 1806-9959

Braz. J. Bot. vol.35 no.4 São Paulo  2012 



Influence of air temperature on proteinase activity and beverage quality in Coffea arabica



Hellen Marília Couto de AbreuI; Paula Macedo NobileI,II; Milton Massao ShimizuI; Paula Yuri YamamotoIII; Emerson Alves SilvaIV; Carlos Augusto ColomboIII; Paulo MazzaferaI,*

IUniversidade Estadual de Campinas, Instituto de Biologia, Departamento de Biologia Vegetal, Laboratório de Fisiologia Vegetal, Caixa Postal 6109, 13083-970 Campinas, SP, Brazil
IIInstituto Agronômico de Campinas, Centro de Cana, Caixa Postal 206, 14001-970 Ribeirão Preto, SP, Brazil
IIIInstituto Agronômico de Campinas, Centro de Recursos Genéticos Vegetais, Caixa Postal 28, 13012-970 Campinas, SP, Brazil
IVInstituto de Botânica, Núcleo de Pesquisa em Fisiologia, Caixa Postal 68041, 04045-972 São Paulo, SP, Brazil




Fruits were collected from trees of Coffea arabica cv. Obatã grown at Mococa and Adamantina in São Paulo State, Brazil, which are regions with marked differences in air temperature that produce coffee with distinct qualities. Mococa is a cooler location that produces high-quality coffee, whereas coffee from Adamantina is of lower quality. The amino acid and protein contents, amino acid profile, and proteinase activity and type in endosperm protein extracts were analysed. Proteinase genes were identified, and their expression was assayed. All results indicate that temperature plays a role in controlling proteinase activity in coffee endosperm. Proteinase activity was higher in the endosperm of immature fruits from Adamantina, which was correlated with higher amino acid content, changes in the amino acid profile, and increased gene expression. Cysteine proteinases were the main class of proteinases in the protein extracts. These data suggest that temperature plays an important role in coffee quality by altering nitrogen compound composition.

Key words: amino acids, coffee quality, cysteine proteinase, endosperm, protein




Coffee is cultivated in more than 80 countries and it is one of the five most important crops exported by developing countries worldwide (Marcone 2004). In recent years the coffee market is demanding increased beverage quality and, as a consequence, studies focusing on beverage quality in areas from crop management to the development of cultivars with different chemical characteristics are being performed (Decazy et al. 2003).

Beverage quality is the final result of interactions among a large number of compounds present in the endosperm (Clifford 1985). After roasting, the coffee flavour and aroma are formed by a complex set of transformations involving sugars, amino acids, peptides, trigonelline, chlorogenic acids, organic acids, lipids and carotenoids as precursors (Montavon et al. 2003).

In addition to these compounds, interactions between reducing sugars and the amino groups of some amino acids, peptides and proteins during the roasting process (the Maillard reaction) are essential for flavour and aroma development (Reineccius 1995). The Maillard reaction is known to be responsible for aroma production as well as for the production of the dark colours in different types of food through the formation of several types of compounds, including pyrazines, pyridines and furans. Most of the data available on the chemical process related to this reaction were obtained by investigating the interaction between reducing sugars and free amino acids (Ho et al. 1993), and highlight the importance of the study of free amino acids and protein profiles in immature coffee beans, which contain all of the precursors needed to develop the final beverage flavour and aroma (Montavon et al. 2003).

In this context, proteinases play a key role in beverage quality development because they alter the seed protein profile, which is likely related to flavour and aroma (Ludwig et al. 2000). Montavon et al. (2003) suggested that the levels of peptide and protein degradation among coffee beans vary with quality differences and that these variations most likely result from the activities of different endogenous proteinases in different beans. Despite the evidence of a relationship between coffee beverage quality and protein profile, there is no concrete evidence that the coffee seed storage proteins that act as aroma and flavour precursors are degraded by specific proteinases (Montavon et al. 2003). Bidimensional electrophoresis analyses of coffee seed protein extracts have identified low molecular weight peptides that are most likely produced by the action of proteinases that degrade the α subunit of the 11S storage protein (Rogers et al. 1999, Ludwig et al. 2000, ). The 11S component is the major storage protein found in coffee seeds, and it participates in amino acid and nitrogen mobilisation for germination and the initial growth of seedlings (Shimizu & Mazzafera 2000). Recently, Lepeley et al. (2012) isolated two cysteine proteinases and four inhibitory gene sequences from C. canephora beans, and showed that proteinase expression increased in the beans of fruits as they matured; the expression of both genes was highest at the ripe stage (red stage), but CcCP1 exhibited 600% higher expression than CcCP4. These authors also showed that recombinant CcCP4 had protease activity against BSA, and assays using a specific inhibitor showed that CcCP4 is a cysteine proteinase.

Some reports have shown that climate may have a major influence on coffee beverage quality by altering the chemical constitution of the seeds. Decazy et al. (2003) studied coffee quality in different environments in Honduras and showed that high altitudes and rainfall less 1,500 mm have favourable effects on the sensorial quality of the beverage by promoting the production of larger beans with higher lipid contents. Air temperature was the main climate factor that affected the sensory profiles of 16 green coffee samples from different locations in Réunion Island. Samples from warmer regions showed major defects in the sensory analysis, whereas positive attributes were observed in samples grown in in colder regions (Bertrand et al. 2012).

In Brazil, the optimal growth temperature for proper coffee fruit development and high-quality beverage production is between 18 ºC and 22 ºC (Alègre 1959, Camargo et al. 1992). Moreover, high temperatures also lead to faster coffee bean ripening, which leads to smaller and denser fruit seeds (Silva 2004, Silva et al. 2005).

The planted coffee cultivation area in Brazil is substantially large, and it comprises several climate conditions. Ortolani et al. (2000) studied the main coffee production regions of the State of São Paulo and found that multiple thermic and water conditions and their interactions (arising from the continentality gradient and altitude variations between 400 and 1,100 m) interfere with coffee tree phenology and determine beverage quality.

Sensorial analyses have shown that coffee beans from Adamantina (São Paulo State), where the annual mean temperature is approximately 24 ºC, provide lower beverage quality than beans from Mococa (São Paulo State), which has an annual mean temperature of 22.5 ºC that is closer to the temperature that is considered adequate for coffee production (Ortolani et al. 2000, 2001, Silva et al. 2005). Thus, the present study evaluated quantitative and qualitative aspects related to coffee proteinases of beans from these regions to establish a relationship between endogenous coffee proteinases, beverage quality and temperature in the planting region. The protein, amino acid and phenolic compound contents were analysed, proteinase genes were isolated and the expression of these proteinases was verified in coffee seeds from Adamantina and Mococa.



Climate data and plant material

The sampled coffee trees were cultivated at the Experimental Stations of the Agronomic Institute of Campinas in Adamantina (21º41' S, 51º05' W and altitude 443 m) and Mococa (21º28' S, 47º01' W and altitude 663 m), which are both in the state of São Paulo. The trees were of the species Coffea arabica cv Obatã IAC 1669-20, and they were 4 years old and grown as a 2.5 × 1.0 m spaced hedgerow. The trees were irrigated with a surface drip irrigation system that provided 4 mm of water per day. The irrigation value was determined based on the mean daily evapotranspiration at Adamantina (3.8 mm) and Mococa (3.2 mm). Therefore, these plants were not drought-stressed.

Climate data (temperature) were obtained from the Integrated Centre of Agrometeorological Information ( According to the Köppen International Classification (Russo Junior 1984), the macroclimates of both sites are Cwa, and the usual annual mean temperatures and total rainfall for Adamantina and Mococa are 23.1 ºC and 21.8 ºC and 1165 and 1442 mm, respectively. The soils of the localities are classified (Staff 1999) as Rhodic eutrustox (Adamantina) and Typic hapludult (Mococa) (Prado 2003).

Fruit harvest

Immature and mature fruits were harvested in 2005. Immature fruits were harvested in the third week of January in Adamantina and in the first week of March in Mococa, whereas mature fruits were harvested in the third week of April in Adamantina and in the first week of July in Mococa. The difference in harvesting period resulted from the 1-2 month difference in maturing rhythm in both locations; maturation is faster in Adamantina (Ortolani et al. 2000, 2001). When harvested, the immature cherries had already reached their maximum size, and the endosperm occupied almost the entire interior of the fruit. For a better indicator of the fruit development in both locations, we determined the dry mass percentages of the whole fruits, perisperm, pericarp and endosperm, and green fruits were collected when the endosperm had approximately 40-45% dry mass (Geromel et al. 2006). Mature fruits presented an intense red colour, and the endosperm had approximately 30-35% dry mass at harvesting. Immediately after handpicking, the fruits were frozen in liquid N2 and then stored in a -80 ºC freezer. For the analyses, cherries were divided into halves with a razor blade, and the endosperm was separated using a scalpel and placed in liquid N2. A portion of the endosperms were lyophilised for biochemical analysis, and another portion was kept in a -80 ºC freezer for protein and RNA extraction.

Biochemical analysis

Lyophilised endosperms were macerated in liquid N2 and extracted in 70% ethanol (50 mg/500 µL) for 1 h at 4 ºC with occasional agitation. The solution was centrifuged at 10,000 × g for 20 min, and the free amino acid content of the resulting supernatant was determined (Cocking & Yemm 1954). For qualitative amino acid analysis, the milled endosperms were extracted (100 mg/2 mL) in MCW solution [methanol:chloroform:water, 12:5:3, v/v/v (Bielesk & Turner 1966)] at room temperature for 24 h with constant agitation. The solution was centrifuged at 10,000 × g for 15 min, and the supernatant was mixed with 1 volume of chloroform and 1.5 volumes of distilled water, followed by vigorous agitation. After another centrifugation for phase separation, the methanolic-aqueous phase was collected and dried under a speed-vac (Savant), redissolved in water and analysed using HPLC coupled with fluorimetric detection after derivation with o-phthaldialdehyde (Marur et al. 1994).

Proteinase activity

Endosperms from immature and mature fruits were macerated in liquid N2, and protein extraction was performed in 0.1 M Na-phosphate buffer, pH 7.0, with 1% ascorbic acid and PVPP (1/10-1, m/v), using 1 g of endosperm for each 7 mL of solution. Extracts were centrifuged at 12,000 × g for 20 min at 4 ºC, and the supernatant was desalted in PD-10 Sephadex G25 columns (GE HealthCare) pre-equilibrated with 0.1 M Na-phosphate buffer, pH 7.0. The protein concentration in the desalted extract was determined with a ready-to-use Bradford reagent [GE HealthCare, (Bradford 1976)], using bovine serum albumin as a standard. Proteinase activity was determined by adding to this reaction 100 µg of protein, 0.1% azocasein (m/v) and 5 mM DTT in a final volume of 1 mL in Na-phosphate buffer, pH 7.0. DTT was added to all of the reactions because it increases coffee proteinase activity (Paulo Mazzafera, unpublished data). The reaction was performed for 1 h at 37 ºC and then quenched by the addition of 500 µL of 5% trichloroacetic acid. The reaction was centrifuged at 12,000 × g for 10 min, and the supernatant was collected and its absorbance determined at 280 nm using a non-incubated control reaction as a reference sample. The activity was expressed as absorbance at 280 nm h-1 mg-1 protein.

For proteinase class determination, 100 µg of extracted protein was separated on an SDS-PAGE gel (10% acrylamide; Mini-Protean II, Bio-Rad), co-polymerised with 0.15% BSA, under a continuous 12 mA current for 2 h. The gel was quickly washed with distilled water, followed by renaturing buffer (100 mM Tris-HCl, pH 7.5, and 1% Triton X-100) for 20 min to remove the SDS, and finally for 20 min with 100 mM Tris-HCl, pH 7.5 buffer. The gel was then cut vertically into strips, which were placed into separate test tubes with 100 mM Tris-HCl, pH 7.5 buffer containing specific proteinase inhibitors (final concentrations: 10 mM EDTA for metalloproteinases, 15 µM iodoacetamide for cysteine proteinases, 1 µM pepstatin for aspartic proteinases, and 1 mM PMSF for serine proteinases) for 1 h at 37 ºC. After this period, DTT was added to each tube at a final concentration of 5 mM, and the reactions were incubated overnight at 37 ºC with slow agitation. The proteins were stained for 1 h at 37 ºC with 0.1% Coomassie Blue R250 (in an aqueous solution of 45% methanol and 9% acetic acid) and then destained in 7% methanol and 5% acetic acid in water. Activity was verified through the visualisation of unstained regions in the gel because the co-polymerised BSA was digested by proteinase activity.

Proteinase gene isolation

The Coffee Genome EST database – CafEST (Vieira et al. 2006) was searched for the keywords "protease" and "proteinase". The sequences of two cysteine and two aspartic proteinases isolated from beans of Coffea canephora (McCarthy et al. 2007, Lepelley et al. 2012) were also used as baits. More than 600 reads were returned from these searches and used to form contigs in the BioEdit software (Hall 1999), using the CAP3 tool (Xiaoqiu 1992). Then, the contigs were analysed to determine which of them contained the highest number of CafEST reads representing cDNAs from coffee fruits and seeds. The selected contigs were compared with sequences deposited at the NCBI (National Center for Biotechnology Information), and probable open reading frames (ORF) were identified through comparisons with homologous genes from other species. Amino acid sequences were obtained by translating the nucleotide sequences using Swiss-Prot (

Total RNA was extracted from endosperms using the TRIzol reagent (Invitrogen). The RNA was used as a template for the production of first-strand cDNA using the AMV Reverse Transcriptase enzyme (Promega) and the primer B26 (Frohmann et al. 1988). The same amount of RNA was used for all samples.

Phylogenetic trees for the amino acid sequences of coffee cysteine and aspartic proteinases and their homologues were generated with a Neighbour Joining distance matrix using the default parameters in ClustalX (Thompson et al. 1997) and visualised by Mega 3.1 (Kumar et al. 2004).

Proteinase gene expression analyses

Primers for quantitative PCR (qPCR) were designed based on the sequences of the isolated genes (table 1) using the Primer Express tool (Applied Biosystems). The glyceraldehyde-3-phosphate-dehydrogenase gene (GAPDH) was used as an internal control in these analyses (Barsalobres-Cavallari et al. 2009, Cruz et al. 2009). Each reaction contained 2 µL of cDNA (3 ng µL-1), 0.15 mM of each primer (table 1) and 6.25 µL of SYBR Green PCR Master Mix (Applied Biosystems) in a final volume of 12.5 µL. Each sample was processed in triplicate, and a control reaction with no cDNA was performed for each primer combination. The qPCR assays were conducted in an ABI PRISM 7500 Sequence Detection System instrument (Applied Biosystems) under the following conditions: 50 ºC for 2 min and 95 ºC for 10 min, followed by 40 cycles at 94 ºC for 15 s and 60 ºC for 1 min. Two pairs of primers with similar behaviour were designed for each sequence. The relative quantification was determined by the 2-ΔΔCt method (ΔCt = Cttag – Ctref), where Ct is the threshold cycle, tag is the tagged gene, and ref is the reference gene (Livak & Schmittgen 2001).

Statistical analysis

Samples collected from four plants were used in the biochemical analysis. The four samples were combined into two groups (two replicates of two samples) for the gene expression analyses, which were performed in triplicate. The biochemical analysis data were analysed by ANOVA, and means were compared at P < 0.05 using Duncan's test. For expression analysis, only means were calculated, although the standard deviation in each sample (i.e., among the six technical replicates) was less than 4%.



Mococa and Adamantina climate data

The maximum and minimum monthly mean temperatures registered for the years of 2004 (when the coffee plants flowered) and 2005 showed that Adamantina experienced higher temperatures than Mococa, even during the winter (figure 1). In Adamantina, the average maximum temperatures were higher than 30 ºC for several months, but this occurred only occasionally in Mococa. Moreover, from August 24, 1992 to August 10, 2007, the mean maximum temperatures were 30.4 ºC and 28.7 ºC at Adamantina and Mococa, respectively, whereas the mean minimum temperatures were 17.8 ºC and 16.9 ºC. Thus, Adamantina consistently has a higher temperature than Mococa.



Biochemical analysis

The highest concentrations of free amino acids were found in the endosperm of immature coffee beans at both sites, and these concentrations decreased with maturation (figure 2A). Immature endosperm from Adamantina showed a higher amino acid content than that from Mococa, but no significant difference at maturation was found.

The most abundant amino acids in the immature and mature endosperm were aspartic acid (Asp), glutamic acid (Glu), asparagine (Asn), serine (Ser), glutamine (Gln), glycine (Gly) and lysine (Lys) (figures 2B and 2C), which together accounted for more than 60% of the amino acids identified; Asn was the most abundant amino acid. Only three amino acids (Asp, Asn and Lys) were present at significantly higher concentrations in the Adamantina endosperm when compared with the Mococa endosperm at the immature stage (figures 2B and 2D). At maturation, more amino acids were present at higher levels in the Adamantina endosperm: Glu, Asn, Lys, alanine (Ala), tyrosine (Tyr), methionine (Met), leucine (Leu) and gamma-aminobutyric acid (GABA) (figures 2C and 2E). Interestingly, in plants from both sites, there was a reduction in the Asn and Gln content from the immature to mature stages, whereas an increase in Ser, valine (Val), phenylalanine (Phe), isoleucine (Ile) and GABA was observed.

Data on soluble proteins were obtained from the extracts prepared for proteinase activity analysis (figure 3A). No difference was observed between immature and mature samples from Adamantina, but immature and mature samples from Mococa exhibited differences. The proteinase activity was clearly higher in immature endosperm than in mature endosperm (figure 3B), and the highest values were observed for immature endosperm from Adamantina. However, despite an almost four-fold difference between immature and mature endosperms, the proteinase activity was similar in mature endosperm from both sites. These same protein extracts were used in SDS-PAGE co-polymerised with BSA to identify the proteinase classes present in coffee endosperm. However, because of the low activity in mature fruit samples, only immature fruit samples were used (figure 3C). Because the results were similar for Adamantina and Mococa extracts, only the results obtained with Adamantina extracts are shown. The strong inhibition of extract protease activity by iodoacetamide demonstrates the predominance of cysteine proteinases in the extracts, but the protease activity was also decreased by PMSF, which indicates some serine proteinase activity. Neither pepstatin nor EDTA affected the protease activity, which indicates the absence of aspartic and metalloproteinase activity, respectively.



Proteinases sequence analysis and gene expression

The CafEST database was searched for proteinases using sequence baits and keywords (protease and proteinase). Many sequences (639 reads) were returned, forming 41 contigs (615 reads) and 24 singlets. Fourteen contigs included sequences (reads) from cDNA libraries generated from fruit tissues, and these reads comprised approximately 4% to 72% of the sequences in each contig. Only three contigs identified as cysteine proteinases (CaCP1 = 71.4%, CaCP4 = 62.5%, CaCP23 = 33.3%) and one aspartic proteinase (CaAP2 = 12%) were chosen. Among all contigs and singlets, only one contig, assembled by only two reads from a leaf cDNA library, was identified as encoding a serine proteinase. Cysteine proteinases were predominant. Among the 41 contigs, 34 were identified as encoding cysteine proteinases, 6 as encoding aspartic proteinases and one as encoding a serine proteinase.

When the contigs were analysed to determine which of them contained the highest number of CafEST reads representing cDNAs from coffee fruits and seeds, we selected three cysteine proteinase contigs, i.e., CaCP1 (JU319518), CaCP4 (JU319519), CaCP23 (JU319517), and one aspartic proteinase contig: CaAP2 (JU319520).

The phylogenetic tree built from the amino acid sequences of the three cysteine proteinases from C. arabica and those from C. canephora (McCarthy et al. 2007, Lepelley et al. 2012) and sequences of homologous proteins from other species showed the formation of two large groups (figure 4A). CaCP1 belonged to the first large group, whereas CaCP4 and CaCP23 belonged to the second large group. Although these proteinases are from the same class and have proteinase domains from the cysteine family (the C1A subfamily of papain proteinases), the grouping tree clearly shows that CaCP1, CaCP4 and CaCP23 belong to different subgroups and are more closely related to sequences from other species than they are to each other. However, CaCP1 and CaCP4 were highly similar to CcCP1 and CcCP4 from C. canephora, respectively. Table 2A shows the similarity between coffee cysteine proteinases and protein sequences from other species.



Alignments of complete sequences with homology to coffee proteinase unigenes provide a better view of the conserved regions (figure 5), which reflect the grouping shown in figure 4A. One interesting observation is that CaCP23 is grouped together with genes that contain the granulin domain, which is not present the other groups (figure 5).

The phylogenetic tree in figure 4B shows that the amino acid sequences of the CcAP2 (McCarthy et al. 2007) and CaAP2 aspartic proteinases are similar, and both belong to a completely different group than CcAP1. The identity between CaAP2 and CcAP1 is only 12% (table 2B), despite their homology within the eukaryotic aspartyl proteinase domain (Asp) region (pfam – PF00026) (figure 6).

The expression analysis of the identified contigs did not show any clear pattern. Figure 7A shows the ratios of proteinase expression in the endosperm of immature and mature fruits compared between sites. In general, proteinase expression was higher in the endosperm from immature fruits. CaCP4 was the most highly expressed gene in the Mococa fruits, whereas the CaCP1 gene was more highly expressed in mature fruits than in green fruits in both Mococa and Adamantina. Figure 7B shows the proteinase expression ratios in Adamantina and Mococa. Proteinase expression was generally higher in Adamantina. The CaCP4 gene showed the greatestlargest differences in expression; it was most highly expressed in mature fruits from Adamantina and in green fruits from Mococa. CaCP23 was more highly expressed more in green fruits from Adamantina than in those from Mococa, whereas the opposite pattern was observed for CaCP1.




Among the compounds suggested to be involved in coffee beverage quality, amino acids and proteins play an important role (Clifford 1985, Rogers et al. 1999, Montavon et al. 2003). Nevertheless, the proportion and concentration of these compounds and how they interact during roasting to influence quality remains to be elucidated (Montavon et al. 2003).

The genetic background (Carvalho 1988, Leroy et al. 2006) and factors related to cultivation (e.g., fertilisation or plague and disease control) certainly influence the types and amounts of compounds stored in coffee seeds (DaMatta & Ramalho 2006, Geromel et al. 2006), but the post-harvest process may also influence beverage quality (Clarke 1985, Vincent 1985). After harvesting, coffee fruits may be dry- or wet-processed (Clarke 1985, Vincent 1985), and significant metabolic changes may occur in the living seed during the processing steps (Bytof et al. 2000, Knopp et al. 2006). Thus, genetic factors, management techniques and post-harvesting processing all contribute to the complex changes in the biochemical composition of coffee seeds. The composition and concentrations of the compounds are then further chemically changed during roasting, which causes many chemical interactions among compounds, such as the Maillard reaction among N compounds (amino acids and proteins) and sugars (Leloup et al. 1995, Montavon et al. 2003, Bertrand et al. 2012).

In addition to these factors, the environmental conditions in which coffee trees are grown have an impact on coffee beverage quality (Decazy et al. 2003, Silva et al. 2005, Bertrand et al. 2012). In Brazil, the time required for coffee fruit maturation changes drastically, differing by up to two months depending on the environment in which coffee is grown (Ortolani et al. 2000, 2001, Silva et al. 2005). Maturation is slower in regions with lower temperatures, and this property has been related to higher coffee quality (Ortolani et al. 2000, Bertrand et al. 2012). Although never tested, it has been proposed that slower maturation provides the time required for the biosynthesis of the adequate proportions of all compounds involved in coffee quality (Silva et al. 2005). Similarly, it has been suggested that coffee trees cultivated under the shadows of other trees undergo slower and more uniform ripening, which allows the fruits to be developed in a more balanced manner and leads to better coffee quality (Muschler 2001). For both of the sites selected in this study, the difference in fruit ripening time is at least one month but can be greater depending on weather variations (Ortolani et al. 2000, 2001). Adamantina produces lower-quality coffee when compared with Mococa (Ortolani et al. 2000, 2001, Silva et al. 2005).

The mean temperatures in Adamantina and Mococa during 2004 and 2005 showed a marked difference that was even more consistent when the 15-year average was calculated (1992 to 2007). This temperature difference is likely related to altitude, as Adamantina is located at 443 m and Mococa is located at 663 m. Beans from coffee trees grown at higher altitudes in Honduras produced a beverage with superior quality (Decazy et al. 2003), which could be explained by the inverse relationship between altitude and temperature.

The annual precipitation (rainfall) in 2004 and 2005 was 1377 and 1171 mm in Adamantina and 1892 and 1389 mm in Mococa, respectively. Both locations have a dry winter season, with nearly no precipitation. For this reason, the coffee plants were kept under irrigation. However, plants from the same plots in Adamantina and Mococa were used in a previous study (Silva et al. 2005) that showed that temperature had greater influence than water availability on beverage quality. This study also confirmed the findings of previous studies (Ortolani et al. 2000, 2001) that showed that coffee beans from Mococa were of higher quality than those from Adamantina. Moreover, the using main component analysis showed a large difference in the amount of nitrogen compounds and proteinase activity between these two sites (Silva et al. 2005).

Free amino acids are among the most important compounds in defining the final quality of coffee (Macrae 1985). Amino acids react with reducing sugars in the Maillard reaction during roasting to produce compounds related to aroma and flavour (Arnoldi 2004). This study showed that the highest concentration of free amino acids occurred in immature coffee samples from Adamantina; the levels of free amino acids were reduced such that the contents in the mature endosperm were similar in seeds from the two sites tested. Silva et al. (2005) used the same experimental coffee plots in Mococa and Adamantina that we used here and also did not find any difference in the free amino acid contents of seeds from mature fruits (sun dry-processed). We suggest that the lower amino acid content in endosperm from mature fruits may simply indicate a decrease in the metabolic rate that reflects a more advanced developmental stage (Sano & Kawashima 1982, Emmanuel 1983). However, the higher content in immature endosperms from Adamantina may indicate a faster metabolism, although the fruits collected from both sites had endosperm of a similar size (dry weight mass).

The analysis of the amino acid profile showed marked differences between the samples from Adamantina and Mococa. However, for most of the amino acids, individual variations are difficult to explain in the light of the knowledge available on the physiology of coffee maturation. The available information is usually related to alterations that occur during roasting. Thus, depending on the roasting conditions, Asn and Gln may undergo spontaneous deamination as free amino acids or as protein residues (Reineccius 1995). Asn is found in higher amounts in samples from Adamantina. In the presence of heat, e.g., during the roasting process, Asn and Gln deamination leads to the formation of Glu and Asp to release ammonia. This free, reactive ammonia may undergo a series of reactions that result in its combination with products from sugar degradation and lead to the formation of pyrazines (Ho et al. 1993), which are among the compounds responsible for the roasted coffee aroma. However, high amounts of pyrazines interfere with beverage flavour (Ho et al. 1992). The aroma produced by pyrazines is complex and depends on their concentration and also on the influence of synergic and antagonistic effects (Dart & Nursten 1985). Thus, our data suggest that the increase in the amount of Asn in samples from Adamantina compared with the amount found in Mococa could lead to pyrazine production and interfere with the quality of the beverage produced by coffee from this region.

Although it was not among the most abundant amino acids and was present at similar levels in immature endosperm from both sites, GABA showed a marked increase in the endosperm of mature fruits from Adamantina. This non-protein amino acid has been studied largely because it accumulates in plant tissues under biotic and abiotic stress conditions (Shelp et al. 1999). Coffee endosperm accumulates GABA during dry processing because of the decrease in water content (Bytof et al. 2004). Kramer et al. (2010) noted complex changes in GABA levels after harvesting and during dry-processing; these changes are related to dehydrin gene expression, which is associated with water stress in coffee beans. These data are supported by the finding that heat seems to cause a considerable increase in the concentration of GABA in plants relative to other types of stress (Shelp et al. 1999, Kinnersley & Turano 2000).

Soluble protein analysis indicated a lack of differences between immature endosperms, but protein accumulation was significantly higher in the endosperm of mature fruits from Mococa. Coffee from the Mococa region produces a better beverage than that from Adamantina (Ortolani et al. 2000, 2001, Silva et al. 2005), and one hypothesis for this observation, as suggested by Silva et al. (2005), is that the higher proteinase activity in fruits from Adamantina breaks down proteins that are important for the development of coffee aroma and flavour.

Proteinase assays demonstrated higher activity in endosperm from immature fruits when compared with mature fruits, which partially explains the higher amount of free amino acids present in immature endosperms. It might be expected that high proteinase activity should be negatively correlated with protein content and vice versa, as observed in endosperm from Mococa. However, although the proteinase activity and amino acid content of endosperms from Adamantina fit this relationship, immature and mature endosperm showed similar contents. Silva et al. (2005) also observed an inverse correlation between proteinase activity and protein content in dry-processed beans from Mococa and Adamantina but did not analyse immature fruits. We did not perform bi-dimensional electrophoresis, but it is possible that the protein profiles of samples from each site were different despite the similar protein contents of the samples.

Endoproteinases are the first proteinases to act on proteins, producing smaller peptides that are then hydrolysed to free amino acids by exopeptidases (Callis 1995). Coffee protein extracts were analysed to characterise endoproteinase classes using polyacrylamide gels co-polymerised with BSA and then incubated with specific inhibitors for each proteinase type: pepstatin A for aspartic proteinases, PMSF for serine proteinases, EDTA for metalloproteinases and iodoacetamide for cysteine proteinases. Enzymatic activity was characterised by the presence of negative bands (no colour development), which indicates that the co-polymerised BSA was degraded by enzymatic action. Consistent with the spectrophotometry results, the proteinase activity in the endosperm of mature coffee fruits was very low and could not be properly detected by electrophoresis. Thus, characterisation was performed in extracts from immature endosperms.

In gel activity assays identified cysteine proteinases to be the predominant type of endopeptidase in coffee endosperm, but serine proteinases were also detected. In contrast, although we detected in gel serine proteinase activity, no serine proteinase sequence was identified in our search of the CafEST database. However, this search was performed before EST data for C. canephora fruits (Leroy et al. 2005) had been incorporated into the CafEST (Mondego et al. 2011). Thus, we did not expect to find homologous proteinase genes from C. canephora (McCarthy et al. 2007, Lepelley et al. 2012).

The CafEST database search for proteinases returned a large number of sequences (reads), which were grouped by similarity to form contigs. Contigs with a high proportion of reads from fruit cDNA libraries were chosen for further studies. We identified a massive predominance of cysteine proteinases, followed by aspartic proteinases; the CafEST database yielded only one contig for serine proteinase that was formed only by two sequences (reads) from a leaf cDNA library. The analysis of ESTs from C. arabica and C. canephora together showed that the most widely expressed contigs in C. arabica encode a papain-like cysteine proteinase (Mondego et al. 2011). However, these data should be interpreted cautiously because we selected only contigs generated from fruit cDNA libraries. One possible reason for the lack of correspondence between the in gel characterisation and the absence of serine proteinase genes is that the fruits collected here and those used to produce the cDNA libraries in the coffee EST database may not have been at the same stage of development. Additionally, the CafEST included only two libraries generated from fruits of C. arabica, and the stage at which these fruits were collected was not specified (Vieira et al. 2006). In wheat grains, the appearance of different proteinase activities is controlled temporally; serine proteinases are detected at early stages, whereas aspartic proteinases and metalloproteinases are present at later stages (Dominguez & Cejudo 1996). Furthermore, proteinase inhibition may be substrate-dependent, as observed in many microorganisms (Coradi & Guimarães 2006), and metalloproteinase activity may have been observed if substrates other than BSA had been tested. However, based on the activity characterisation and the number of contigs encoding cysteine proteinases, it is evident that this class of endopeptidases is the most abundant in coffee endosperm.

Our search for proteinase genes in fruit cDNA libraries revealed four sequences, and a comparison with sequences deposited on the NCBI database indicated that these four sequences corresponded to three cysteine proteases (CaCP1, CaCP4 and CaCP23) and one aspartic proteinase (CaAP2). Two cysteine proteinase genes (CcCP-1 and CcCP-4) and an aspartic proteinase gene (CcAP-2) isolated from C. canephora (McCarthy et al. 2007, Lepelley et al. 2012) encode proteins with 97 to 99% similarity to the two cysteine proteinases and aspartic proteinase of C. arabica identified here, which strongly suggests that these genes are orthologous. For this reason, the orthologous genes from C. arabica (CaCP1, CaCP4 and CaAP2) were named after the C. canephora genes.

To better understand the relationships among the proteinases studied, we built a phylogenetic tree that included the predicted amino acid sequences of coffee cysteine proteinases and similar sequences deposited in the NCBI protein database. This tree allowed us to categorise each gene that we identified into well-defined subgroups and showed that proteinases containing domains from the cysteine family, particularly from the C1A subfamily (papain proteinases), contained differences in other regions that enabled their classification into distinct groups. The alignment of the predicted amino acid sequences of the identified contigs with some complete sequences that had similarity to coffee proteinases sequences allowed us to better visualise these different regions.

The papain family includes enzymes with a large range of activities, including large-spectrum endoproteinases such as papain, aminopeptidases, dipeptide peptidases and enzymes with exo- and endopeptidase activities (Rawlings et al. 2008). The phylogenetic tree clearly shows that a single plant species may express proteinases from different subgroups [e.g., Phaseolus vulgaris (groups 1 and 3), Vitis vinifera (groups 2 and 3), Lycopersicum esculentum (groups 2 and 4) and Glycine max (groups 1 and 2)]. In G. max, for instance, the sequences grouped with the CaCP1 and CaCP4 proteinases present very dissimilar functions. The G. max sequences homologous to CaCP1 are induced by water stress (Nong et al. 1995), whereas the sequence homologous to CaCP4 is related to senescence (Ling et al. 2003).

CaCP23 belongs to a group that contains the granulin domain, which is not found in the other groups). This domain may have several biological functions, is most likely activated by post-translational proteolytic processing and is most often found in metazoans (Bhandari et al. 1992). In plants, this domain is usually related to the C-terminal region of cysteine proteinases belonging to the papain subfamily. The gene tdi-65, isolated from the tomato, is phylogenetically related to CaCP23 and is induced by water stress but not by ABA, which suggests a relationship with senescence and cell death (Harrak et al. 2001).

The subgroup that includes the protein CaCP4 (subgroup 1, figure 4A) presents a conserved KDEL sequence at the C-terminus, which controls the transport of the protein from the endoplasmic reticulum to protein storage vacuoles (Toyooka et al. 2000). This same subgroup contains some previously characterised genes, such as SH-EP (sulphydryl endoproteinase), which encodes a cysteine proteinase (Vm445927) that is involved in the degradation of storage globulin in germinating seeds and in the early development of ripening stage fruits in Vigna mungo (Yamauchi et al. 1992). This finding is particularly interesting because the 11S globulin is the main storage protein in coffee seeds (Acuña et al. 1999, Marraccini et al. 1999, Rogers et al. 1999). The electrophoretic profile of protein extracts shows that this storage protein is predominant in several cultivars and coffee species (Baú et al. 2001).

Although we studied only four contigs, i.e., those with the highest proportion of reads from cDNA libraries, our qPCR expression analysis showed good agreement with the proteinase activity assays because the highest gene expression was observed in endosperm from green fruits. CaCP4 was the most highly expressed gene in the immature endosperm and in fruits from Mococa. CaCP1 was not expressed at similar levels in Adamantina and Mococa, and it was expressed at higher levels in mature endosperm than in immature endosperm. CaCP23, which has not been described in previous reports, was most highly expressed in immature endosperms from Adamantina. CaCP4 was the most differentially expressed gene. Lepelley et al. (2012) observed that CcCP1 was more highly expressed than its orthologue CcCP4 throughout the fruit maturation process in Coffea canephora, in contrast to our data, with highest expression of both genes at the mature stage (red fruits). Our in gel activity also showed that the protease activity was highest in immature endosperm. These differences may reflect differences between the coffee species (C. arabica and C. canephora) used in these studies as well as the regions in which the coffee trees were grown. The fruits used by Lepelley et al. (2012) were harvested from plants in the field in Ecuador, and no further information was given.

The CaAP2 gene is orthologous to the CcAP2 gene from C. canephora, and its expression level was similar in coffee roots, pericarp and endosperm, but its expression in the mature fruit pericarp was higher than that in other tissues and developmental stages (McCarthy et al. 2007). CaAP2 and CcAP2 belong to the peptidase A1 family, and some of their homologs have been reported as responsive to wounding or pathogen infection and are expressed in different tissues such as leaves, roots and seeds (Asakura et al. 1995, Schaller & Ryan 1996, Terauchi et al. 2004, Guevara et al. 2005, Huang et al. 2009). CaAP2 was not significantly differentially expressed between mature and immature endosperm or between plants grown at different sites.

It is clear from our and others' results that comparisons between gene expression and enzymatic activity for coffee proteinases must be analysed carefully because some proteinase genes may not have been identified, whereas activity data reflect the activity of all expressed genes. Nevertheless, the joint analysis of enzymatic activity data and gene expression demonstrates that the activities of these proteinases are quite complex. The finding that some of the proteinase genes identified in coffee are similar to proteinase genes that are modulated by stress in other plants suggests that further studies may define the role of each enzyme according to the environmental variations that occur during each phase of coffee fruit development and maturation. It is important to consider that immature fruits were harvested in January (Adamantina) and March (Mococa), which are the months in which the highest temperatures were registered and thus may lead to heat stress conditions. Therefore, our and others' results (Decazy et al. 2003, Lepelley et al. 2012) suggest that the increased activity and proteinase expression during these months may be related to heat stress because the plants were irrigated and thus were not water-stressed.

Environmental factors have a strong influence on coffee beverage quality by changing the amino acid and protein profile, which is an important factor in coffee quality. Proteinase activity is higher in coffee beans from warmer places, which can change the protein and amino acid composition and thus change the quality. Therefore, a relationship seems to exist among temperature, proteinase activity and coffee quality. This information, together with other data on temperature and coffee composition, helps to explain why coffee from regions with low temperatures has higher quality.

It is believed that the high quality of coffee produced in colder climates is related to the time required for complete maturation, which enables the biosynthesis of substances that are important for the development of aroma and flavour. However, there is no concrete proof for this assumption, and the different composition of coffee beans from locations with different mean temperatures is the only and indirect evidence supporting this theory. In this work, we showed that temperature modulates proteinase activity and expression in endosperm of coffee fruits, which leads to variations in the amounts and composition of amino acids and proteins. More detailed proteomics studies will show whether differences in proteinase activity among locations significantly alter the protein profile of coffee endosperm or the types of protein cleaved by these enzymes, and whether the amino acid compositions of the peptides generated would lead them to take part in the Maillard reaction and consequently alter the beverage quality of coffee.

Acknowledgements – Hellen M.C. Abreu & Paula Y. Yamamoto received fellowships from Capes-Brazil; Paula M. Nobile & Milton M. Shimizu received post-doctoral fellowships from Consórcio Brasileiro de Pesquisa e Desenvolvimento do Café; and P. Mazzafera & Carlos A. Colombo received researcher fellowships from CNPq-Brazil (CNPq). This work was sponsored by the Consórcio Brasileiro de Pesquisa e Desenvolvimento do Café.



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(received: November 07, 2012; accepted: November 26, 2012)



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