Aluminum-induced proteomic responses in Qualea dichotoma (Mart.) warm: a dataset descriptive analysis

Abstract

Aluminum (Al) toxicity in acidic soils is a major constraint on global crop production. In contrast, native species of the Brazilian Savanna (Cerrado), such as Qualea dichotoma Mart. & Warm. (Vochysiaceae), have not only adapted to these conditions but exhibit an Al requirement for growth. This species efficiently accumulates Al, even in soils with low Al availability. Despite the significance of Al metabolism in plants, native Al-accumulating species like Q. dichotoma remain understudied, particularly at the molecular level. This study presents the first proteomic analysis of Q. dichotoma leaves from Al-supplemented and non-supplemented plants using label-free mass spectrometry. Our dataset comprises 1,255 proteins identified by querying the Uniprot Myrtales database and 1,062 proteins against the Q. grandiflora genome database. respectively. These findings provide a foundational resource for understanding the role of Al in native plant metabolism and advance our knowledge of plant-metal interactions. The raw data are publicly available via the Centre for Computational Mass Spectrometry (MassIVE ID: MSV000092667). https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=7ae50a0d01d942c78da2caec254093f0.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-40059-8.

Introduction

The Cerrado biome is a promising source of novel genes and proteins with significant biotechnological potential. For instance, studying the physiological role of Al in native species such as Qualea dichotoma Mart. & Warm. (Vochysiaceae), a native Cerrado species, which is metabolically dependent on this metal¹, could provide critical insights for this biome’s conservation. Current agricultural practices, such as liming, negatively impact the Cerrado by altering soil properties and disrupting its unique biodiversity^2,3, especially because Cerrado soils are a key driver of the biome’s ecological richness. Despite its ecological and economic importance – spanning ~ 2 million km² and harboring a wealth of medicinal, pharmaceutical, and biotechnological resources – the Cerrado remains understudied. Its vast genetic heritage and flora are still poorly understood, necessitating further scientific investigation to ensure sustainable resource use.

In acidic soils, aluminum (Al) is toxic to many plants and adversely affects crop productivity. However, certain Cerrado species, including Q. dichotoma, exhibit tolerance to Al and can even benefit from its presence by accumulating high concentrations of the metal⁴. Qualea dichotoma, like all Vochysiaceae species, requires Al for its growth and development. This arboreal species typically reaches a height of 10 to 18 m⁵. The leaves of Q. dichotoma are simple and coriaceous, with a flowering period occurring between October and November⁵. This plant sheds seeds from August to September of the following year⁵. It primarily inhabits dystrophic soils with a pH ranging from 4.5 to 4.7 and base saturation levels of approximately 4% to 5%⁶.

Despite the ecological significance of the Al accumulation phenomenon, biochemical and molecular studies on this phenomenon in native species are still limited^1,2,7–9. Additionally, we conducted a comparative analysis of our results using two public databases — the Uniprot Myrtales and Qualea grandiflora genome databases — to assess the consistency and reliability of the proteomic data, providing a robust foundational dataset for future research. We also emphasize that this work is a descriptive report of the total proteins identified, rather than a quantitative analysis of differential protein expression in response to Al.

Results and discussion

Using PEAKS/PepExplorer software^10,11, we identified 1,255 and 1,062 proteins in Qualea dichotoma leaves based on the Myrtales and Qualea grandiflora translated genome databases, respectively (Fig. 1; Tables S1–S2, Supporting Information). Despite variation in the total proteins identified between the two databases, Gene Ontology (GO) term analysis revealed similar distributions across the three GO categories — molecular function (MF), cellular component (CC), and biological process (BP) — for both the Myrtales and Q. grandiflora genome databases (Fig. 1). However, there were slight discrepancies related to a few GO terms between the two databases (Fig. 1). For instance, in the MF category, the Myrtales database identified the GO term “ATP hydrolysis activity” (3%), whereas the analysis based on the Q. grandiflora genome did not detect this term. Additionally, these small differences were typically associated with protein groups representing a lower percentage of the total proteins, particularly in the Myrtales database (Fig. 1). Another potential factor contributing to these divergences could be the larger number of proteins identified with the Myrtales database (1,255) compared to the Q. grandiflora genome dataset (1,062). Furthermore, while the Myrtales database encompasses proteins from the entire order, the Q. grandiflora genome is restricted to that species. Overall, the current analysis indicated that all GO terms assigned to proteins from the Q. grandiflora genome were also identified in proteins derived from the Myrtales database, with similar proportions of proteins assigned to each corresponding group (Fig. 1).

Fig. 1.

Diagram showing the distribution of identified proteins in Qualea dichotoma (Mart.) Warm. (Vochysiaceae) leaves. The GO terms are organized within the molecular function (A/A’), cellular component (B/B’), and biological process (C/C’) Gene Ontology (GO) categories. The diagrams on the left (A, B, and C) represent the GO terms associated with proteins grouped using the Myrtales database, while those on the right (A’, B’, and C’) represent the GO terms of proteins categorized based on the Qualea grandiflora genome database.

Furthermore, a more detailed analysis of the proteins categorized within these non-corresponding GO terms revealed that they could also be linked to closely related GO terms. For example, the protein glutaredoxin-dependent peroxiredoxin (Punica granatum, A0A6P8DWH7_PUNGR), which was assigned to the “Cellular detoxification” GO term (GO:1990748; Myrtales: Biological Process), can also be associated with GO:0004601 (Peroxidase activity)¹² and GO:0016209 (Antioxidant activity). Notably, all these categories are closely associated with cellular detoxification.

Regarding MF, the identified proteins were predominantly grouped into corresponding GO terms, as illustrated in Fig. 1A and A’. Both databases revealed that the major MF GO terms were “ion binding” and “organic cyclic molecule binding” (Fig. 1A/A’). The proteins categorized under CC were mainly assigned to the following GO terms: “cytoplasm,” “intracellular anatomical structure,” “organelle,” and “membranes” (Fig. 1B/B’). Notably, the “intracellular anatomical structure” GO term encompasses several cellular sites, such as the endoplasmic reticulum (ER) and ribosomes, which may suggest enhanced cellular metabolism in Q. dichotoma leaf cells, necessitating an elevated level of protein synthesis (Fig. 1B/B’ and 3). It is important to note that these GO categories exhibit some overlap. Additionally, the analysis from both databases prominently featured GO terms related to primary metabolism, organic substance metabolism, and the cellular response to stimulus (Fig. 1B).

Fig. 3.

One-hundred-twenty-day old Qualea dichotoma plants (30 days germination + 90 days treatment) cultivated with and without Al supplementation. A Plant grown without Al supplementation on ¹/₅ MS nutritional solution. B Plant supplemented with Al (150 μm of AlCl₃). Scale bar: A, B = 1 cm.

It is important to point out that this research is essential for developing sustainable conservation strategies. This study contributes valuable knowledge to the conservation one of Brazil’s most vital biomes. The biological process (BP) category displayed a pattern consistent with the previous categories, further confirming the high degree of similarity between the two databases (Fig. 1C/C’). The largest BP categories in both databases were associated with the “organic substance metabolic process”, “primary metabolic process”, and “cellular metabolic process” (Fig. 1C/C’). Although the use of a co-generic reference genome provides a high-confidence scaffold for protein identification; this descriptive approach may not capture species-specific proteoforms or novel proteins absent from the current Myrtales databases. Furthermore, these findings characterize the protein inventory of Q. dichotoma but do not account for dynamic post-translational modifications or functional enzymatic activity under varying physiological conditions.

The proteomic analysis of Q. dichotoma leaves identified proteins associated with key metabolic processes and cellular sites (Fig. 2). Several of these proteins were linked to organelles, primary cellular metabolic processes, organic substance metabolism, and responses to stimuli, as well as other essential cellular processes, including protein synthesis, the tricarboxylic acid cycle (TCA cycle), energy production and utilization, and oxidative stress metabolism (ROS – Reactive Oxygen Species).

Fig. 2.

A schematic representation of some metabolic processes and cellular sites associated with the proteins identified in Qualea dichotoma leaf cells. ETC Electron Transport Chain, PM Plasma Membrane, ROS Reactive Oxygen Species, TCA Tricarboxylic Acid Cycle. (Created in https://BioRender.com).

In conclusion, this descriptive proteomic analysis of Q. dichotoma leaves, supported by the Q. grandiflora genome and the Myrtales UniProt database, offers a consistent and expanded view of the proteome within the Myrtales order. By characterizing a native species, a group currently underrepresented in proteomic literature, this study establishes a foundational framework for understanding the specialized mechanisms of aluminum metabolism and accumulation in plants adapted to these unique environments.

Methods

Plant material and growth

Plant material was collected at the reserve of the Brazilian Institute of Geography and Statistics (IBGE), Brasília, Federal District, Brazil, under registration number MCS 4062. A voucher specimen was deposited in the Herbarium of Brasília (UB) and taxonomically identified by Dr. Micheline Carvalho, Department of Botany, University of Brasília. Field collection of Q. dichotoma plant material was performed in compliance with all relevant national and international guidelines. Research was authorized under IBGE Permit #20 and registered with the Brazilian Ministry of Environment (SisBio) under #379,081.

For the experiment, Q. dichotoma seeds were disinfected by immersing them in 70% ethyl alcohol (1 min), followed by treatment with 2% sodium hypochlorite (NaClO) for 30 min, and subsequently washed three times with sterile double-distilled water. The seeds were then germinated in a Gerbox with sterilized Germitest paper and distilled water and incubated in a BOD incubator at 25 °C with an 18-h photoperiod. After 30 days, 80 seedlings (40 per treatment) were selected and transferred to plastic bags containing sterilized vermiculite. The plants were watered every other day with ¹/₅ strength MS nutrient salts, with or without 150 µM aluminum chloride (AlCl₃), at pH 4.8 (± 0.2), 25 °C and with an 18-h photoperiod for 120 days (30 days of germination + 90 days of Al-treatment).

Protein extraction and digestion

Figure 3 shows the phenotype of 120-day-old Q. dichotoma grown with and without Al supplementation. Subsequently, a pool of leaf samples from six plants per treatment (three replicates per treatment) was collected, which were immediately frozen in liquid nitrogen and stored at −80 °C until protein extraction.

For total protein extraction, 100 mg of leaves from each treatment were ground in a mortar with liquid nitrogen, and solubilized in an extraction buffer composed of acetone, 10% trichloroacetic acid (TCA), and 0.07% β-mercaptoethanol, vortexed, and incubated at 4 °C for 3 h. Subsequently, the leaf samples were centrifuged at 10,000 g (20 min), the supernatant was discarded, and the pellet was washed five times with 2 mL of acetone containing 10% TCA. Afterward, the pellet was vacuum-dried and resuspended in rehydration buffer (7 M urea, 2 M thiourea, and 250 mM triethylammonium bicarbonate-[TEAB], pH 8.5). The total protein concentration was determined with the Qubit 2.0 fluorometer (Invitrogen) and its quality checked on a 10% SDS-PAGE gel.

Subsequently, the protein samples were solubilized, reduced, and alkylated before tryptic digestion. Specifically, 200 µg of protein were reduced with 10 mM dithiothreitol (DTT) for 60 min at 56 °C and alkylated with 100 mM iodoacetamide (IAA) for 60 min at 37 °C in the dark. The protein samples were then diluted in 100 mM ammonium bicarbonate (NH₄HCO₃, pH 8.1) and digested with a 2% trypsin solution (PROMEGA) at 37 °C for 16 h. Subsequently, the resulting peptide samples were acidified to a final concentration of 0.1% (v/v) with the addition of trifluoroacetic acid (TFA), centrifuged at 10,000 g (10 min), and desalted using C18 StageTips. The peptides were then vacuum-dried and resuspended in 0.1% formic acid before being analyzed by liquid nano-chromatography coupled to an LTQ Orbitrap Elite mass spectrometer.

Protein analysis

The peptide samples were injected into a chromatographic system (Dionex Ultimate 3000 RSLCnano UPLC, Thermo, Waltham, MA, USA) for reversed-phase nano-chromatography as follows: 1) three technical replicates per treatment (1 µg of peptide) were injected into a trap column (2 cm x 100 μm), containing C18 resin (5 μm particles). The samples were eluted onto the analytical column with a gradient of 2 to 35% acetonitrile and 0.1% formic acid. The chromatographically separated fractions were eluted directly into an LTQ Orbitrap Elite mass spectrometer, which was operated in Data Dependent-Acquisition (DDA) mode, generating MS1 spectra in the Orbitrap analyzer (resolution of 120,000 FWHM at 400 m/z) across a range of 300–1650 m/z and dynamic exclusion of 10 ppm. For each MS1 spectrum, the 15 most intense ions with charges higher than 2 were automatically selected and directed for high-energy collision-induced dissociation (HCD). The configuration for HCD was: 2.0 m/z insulation window with automatic gain control (AGC) target of 1 × 10⁶, 100 ms maximum injection time, collision energy normalized at 35%, and an intensity threshold set at 3000.

Chromatogram alignments were performed using Progenesis QI software. Protein identification and PTM detection were carried out PEAKS 7.0 (Bioinformatics Solutions Inc., Waterloo, ON, Canada) (^10,11) based on the Myrtales and Q. grandiflora translated genome deposited in the NCBI (National Centre for Biotechnology Information) database (BioProject PRJNA786741). Redundant sequences were removed using FASTAtools (https://lbqp.unb.br/LBQPtools/; accessed in March 2023). The search was performed based on de novo and peptide-spectrum match (PSM) sequencing using tolerance of 10 ppm for precursor masses, tolerance of 0.05 Da, for fragment ion masses, up to two missed cleavages, carbamidomethylation of cysteines as fixed modification, and oxidation of methionine as a variable modification. Protein identification was considered significant at a false discovery rate (FDR) less than 1% (FDR < 1%). Gene ontology (GO) annotation was obtained using Blast2go software. Proteomic data are available via MassIVE MSV000092667 https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=7ae50a0d01d942c78da2caec254093f0.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

Natália Faustino Cury – Post-Doc researcher. Experimental design, plant material collection, protein analysis, GC-MS analysis, data interpretation, and writing. Darislene de Sousa Ericeira Moreira - Plant material collection and growth, protein extraction and preparation. Michelle de Souza Fayad André. Post-Doc researcher. Plant material collection and growth, protein analysis. Laísa Maria de Resende Castro – Doctoral student. Plant material collection and growth, protein extraction and analysis, data interpretation. Wagner Fontes – GC-MS analysis, bioinformatics, data interpretation, and writing. Marcelo Valle de Sousa – GC-MS analysis and bioinformatics. Luiz Alfredo Rodrigues Pereira – Leading researcher and corresponding author, data analysis, interpretation, and writing.

Funding

The funding of this research was provided by CAPES, as Doctoral and Post-Doctoral scholarships, and FAP-DF, grants 0193.001622/2017, and 00193–00002089/2023-97. The authors declare neither conflicts nor competing interests and funding.

Data availability

All data is publicly available at the Centre for Computational Mass Spectrometry (MassIVE ID: MSV000092667). [https://massive.ucsd.edu/ProteoSAFe/dataset.jsp? task=7ae50a0d01d942c78da2caec254093f0](https:/massive.ucsd.edu/ProteoSAFe/dataset.jsp? task=7ae50a0d01d942c78da2caec254093f0).

Declarations

Competing interests

The authors declare no competing interests.