A reduced dimensionality NMR pulse sequence and an efficient protocol for unambiguous assignment in intrinsically disordered proteins

Resonance assignment in intrinsically disordered proteins poses a great challenge because of poor chemical shift dispersion in most of the nuclei that are commonly monitored. Reduced dimensionality (RD) experiments where more than one nuclei are co-evolved simultaneously along one of the time axes of a multi-dimensional NMR experiment help to resolve this problem partially, and one can conceive of different combinations of nuclei for co-evolution depending upon the magnetization transfer pathways and the desired information content in the spectrum. Here, we present a RD experiment, (4,3)D-hNCOCAnH, which uses a combination of CO and CA chemical shifts along one of the axes of the 3-dimensional spectrum, to improve spectral dispersion on one hand, and provide information on four backbone atoms of every residue—HN, N, CA and CO chemical shifts—from a single experiment, on the other. The experiment provides multiple unidirectional sequential (i → i ? 1) amide ¹H correlations along different planes of the spectrum enabling easy assignment of most nuclei along the protein backbone. Occasional ambiguities that may arise due to degeneracy of amide proton chemical shifts are proposed to be resolved using the HNN experiment described previously (Panchal et al. in J Biomol NMR 20:135–147, 2001). Applications of the experiment and the assignment protocol have been demonstrated using intrinsically disordered α-synuclein (140 aa) protein.     

Bridge over troubled proline: assignment of intrinsically disordered proteins using (HCA)CON(CAN)H and (HCA)N(CA)CO(N)H experiments concomitantly with HNCO and i(HCA)CO(CA)NH

NMR spectroscopy is by far the most versatile and information rich technique to study intrinsically disordered proteins (IDPs). While NMR is able to offer residue level information on structure and dynamics, assignment of chemical shift resonances in IDPs is not a straightforward process. Consequently, numerous pulse sequences and assignment protocols have been developed during past several years, targeted especially for the assignment of IDPs, including experiments that employ H^N, H^α or ¹³C detection combined with two to six indirectly detected dimensions. Here we propose two new HN-detection based pulse sequences, (HCA)CON(CAN)H and (HCA)N(CA)CO(N)H, that provide correlations with ¹H^N(i ? 1), ¹³C′(i ? 1) and ¹⁵N(i), and ¹H^N(i + 1), ¹³C′(i) and ¹⁵N(i) frequencies, respectively. Most importantly, they offer sequential links across the proline bridges and enable filling the single proline gaps during the assignment. We show that the novel experiments can efficiently complement the information available from existing HNCO and intraresidual i(HCA)CO(CA)NH pulse sequences and their concomitant usage enabled >95 % assignment of backbone resonances in cytoplasmic tail of adenosine receptor A2A in comparison to 73 % complete assignment using the HNCO/i(HCA)CO(CA)NH data alone.     

CSI 2.0: a significantly improved version of the Chemical Shift Index

Protein chemical shifts have long been used by NMR spectroscopists to assist with secondary structure assignment and to provide useful distance and torsion angle constraint data for structure determination. One of the most widely used methods for secondary structure identification is called the Chemical Shift Index (CSI). The CSI method uses a simple digital chemical shift filter to locate secondary structures along the protein chain using backbone ¹³C and ¹H chemical shifts. While the CSI method is simple to use and easy to implement, it is only about 75–80 % accurate. Here we describe a significantly improved version of the CSI (2.0) that uses machine-learning techniques to combine all six backbone chemical shifts (¹³C_α, ¹³C_β, ¹³C, ¹⁵N, ¹HN, ¹H_α) with sequence-derived features to perform far more accurate secondary structure identification. Our tests indicate that CSI 2.0 achieved an average identification accuracy (Q3) of 90.56 % for a training set of 181 proteins in a repeated tenfold cross-validation and 89.35 % for a test set of 59 proteins. This represents a significant improvement over other state-of-the-art chemical shift-based methods. In particular, the level of performance of CSI 2.0 is equal to that of standard methods, such as DSSP and STRIDE, used to identify secondary structures via 3D coordinate data. This suggests that CSI 2.0 could be used both in providing accurate NMR constraint data in the early stages of protein structure determination as well as in defining secondary structure locations in the final protein model(s). A CSI 2.0 web server (http://csi.wishartlab.com) is available for submitting the input queries for secondary structure identification.     

Parallel acquisition of 3D-HA(CA)NH and 3D-HACACO spectra

We present here an NMR pulse sequence with 5 independent incrementable time delays within the frame of a 3-dimensional experiment, by incorporating polarization sharing and dual receiver concepts. This has been applied to directly record 3D-HA(CA)NH and 3D-HACACO spectra of proteins simultaneously using parallel detection of ¹H and ¹³C nuclei. While both the experiments display intra-residue backbone correlations, the 3D-HA(CA)NH provides also sequential ‘i ? 1 → i’ correlation along the ¹Hα dimension. Both the spectra contain special peak patterns at glycine locations which serve as check points during the sequential assignment process. The 3D-HACACO spectrum contains, in addition, information on prolines and side chains of residues having H–C–CO network (i.e., ¹Hβ, ¹³Cβ and ¹³COγ of Asp and Asn, and ¹Hγ, ¹³Cγ and ¹³COδ of Glu and Gln), which are generally absent in most conventional proton detected experiments.     

A 4D HCC(CO)NNH experiment for the correlation of aliphatic side-chain and backbone resonances in 13C/15N-labelled proteins

Summary We recently proposed a novel four-dimensional (4D) NMR strategy for the assignment of backbone nuclei in spectra of ¹³C/¹⁵N-labelled proteins (Boucher et al. (1992) J. Am. Chem. Soc., 114, 2262–2264 and J. Biomol. NMR, 2, 631–637). In this paper we extend this approach with a new constant time 4D HCC(CO)NNH experiment that also correlates the chemical shifts of the aliphatic sidechain (¹H and ¹³C) and backbone (¹H, ¹³C and ¹⁵N) nuclei. It separates the sidechain resonances, which may heavily overlap in spectra of proteins with large numbers of similar residues, according to the backbone nitrogen and amide proton chemical shifts. When used in conjunction with a 4D HCANNH or HNCAHA experiment it allows, in principle, complete assignment of aliphatic sidechain and backbone resonances with just two 4D NMR experiments.     

Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information

We introduce a Python-based program that utilizes the large database of ¹³C and ¹⁵N chemical shifts in the Biological Magnetic Resonance Bank to rapidly predict the amino acid type and secondary structure from correlated chemical shifts. The program, called PACSYlite Unified Query (PLUQ), is designed to help assign peaks obtained from 2D ¹³C–¹³C, ¹⁵N–¹³C, or 3D ¹⁵N–¹³C–¹³C magic-angle-spinning correlation spectra. We show secondary-structure specific 2D ¹³C–¹³C correlation maps of all twenty amino acids, constructed from a chemical shift database of 262,209 residues. The maps reveal interesting conformation-dependent chemical shift distributions and facilitate searching of correlation peaks during amino-acid type assignment. Based on these correlations, PLUQ outputs the most likely amino acid types and the associated secondary structures from inputs of experimental chemical shifts. We test the assignment accuracy using four high-quality protein structures. Based on only the Cα and Cβ chemical shifts, the highest-ranked PLUQ assignments were 40–60 % correct in both the amino-acid type and the secondary structure. For three input chemical shifts (CO–Cα–Cβ or N–Cα–Cβ), the first-ranked assignments were correct for 60 % of the residues, while within the top three predictions, the correct assignments were found for 80 % of the residues. PLUQ and the chemical shift maps are expected to be useful at the first stage of sequential assignment, for combination with automated sequential assignment programs, and for highly disordered proteins for which secondary structure analysis is the main goal of structure determination.     

Backbone chemical shift assignments for <Emphasis Type="Italic">Xanthomonas campestris</Emphasis> peroxiredoxin Q in the reduced and oxidized states: a dramatic change in backbone dynamics

Peroxiredoxins (Prx) are ubiquitous enzymes that reduce peroxides as part of antioxidant defenses and redox signaling. While Prx catalytic activity and sensitivity to hyperoxidative inactivation depend on their dynamic properties, there are few examples where their dynamics has been characterized by NMR spectroscopy. Here, we provide a foundation for studies of the solution properties of peroxiredoxin Q from the plant pathogen Xanthomonas campestris (XcPrxQ) by assigning the observable ¹H^N, ¹⁵N, ¹³C^α, ¹³C^β, and ¹³C′ chemical shifts for both the reduced (dithiol) and oxidized (disulfide) states. In the reduced state, most of the backbone amide resonances (149/152, 98 %) can be assigned in the XcPrxQ ¹H–¹⁵N HSQC spectrum. In contrast, a remarkable 51 % (77) of these amide resonances are not visible in the ¹H–¹⁵N HSQC spectrum of the disulfide state of the enzyme, indicating a substantial change in backbone dynamics associated with the formation of an intramolecular C48–C84 disulfide bond.     

A NMR experiment for simultaneous correlations of valine and leucine/isoleucine methyls with carbonyl chemical shifts in proteins

A methyl-detected ‘out-and-back’ NMR experiment for obtaining simultaneous correlations of methyl resonances of valine and isoleucine/leucine residues with backbone carbonyl chemical shifts, SIM-HMCM(CGCBCA)CO, is described. The developed pulse-scheme serves the purpose of convenience in recording a single data set for all Ile^δ1, Leu^δ and Val^γ (ILV) methyl positions instead of acquiring two separate spectra selective for valine or leucine/isoleucine residues. The SIM-HMCM(CGCBCA)CO experiment can be used for ILV methyl assignments in moderately sized protein systems (up to ~100 kDa) where the backbone chemical shifts of ¹³C^α, ¹³C_β and ¹³CO are known from prior NMR studies and where some losses in sensitivity can be tolerated for the sake of an overall reduction in NMR acquisition time.     

Hash: a program to accurately predict protein Hα shifts from neighboring backbone shifts

Chemical shifts provide not only peak identities for analyzing nuclear magnetic resonance (NMR) data, but also an important source of conformational information for studying protein structures. Current structural studies requiring H^α chemical shifts suffer from the following limitations. (1) For large proteins, the H^α chemical shifts can be difficult to assign using conventional NMR triple-resonance experiments, mainly due to the fast transverse relaxation rate of C^α that restricts the signal sensitivity. (2) Previous chemical shift prediction approaches either require homologous models with high sequence similarity or rely heavily on accurate backbone and side-chain structural coordinates. When neither sequence homologues nor structural coordinates are available, we must resort to other information to predict H^α chemical shifts. Predicting accurate H^α chemical shifts using other obtainable information, such as the chemical shifts of nearby backbone atoms (i.e., adjacent atoms in the sequence), can remedy the above dilemmas, and hence advance NMR-based structural studies of proteins. By specifically exploiting the dependencies on chemical shifts of nearby backbone atoms, we propose a novel machine learning algorithm, called Hash, to predict H^α chemical shifts. Hash combines a new fragment-based chemical shift search approach with a non-parametric regression model, called the generalized additive model, to effectively solve the prediction problem. We demonstrate that the chemical shifts of nearby backbone atoms provide a reliable source of information for predicting accurate H^α chemical shifts. Our testing results on different possible combinations of input data indicate that Hash has a wide rage of potential NMR applications in structural and biological studies of proteins.     

Backbone and side-chain 1H, 15N and 13C assignment of apo- and imipenem-acylated l,d-transpeptidase from Bacillus subtilis

The d,d-transpeptidase activity of Penicillin Binding Proteins (PBPs) is essential to maintain cell wall integrity. PBPs catalyze the final step of the peptidoglycan synthesis by forming 4 → 3 cross-links between two peptide stems. Recently, a novel β-lactam resistance mechanism involving l,d-transpeptidases has been identified in Enterococcus faecium and Mycobacterium tuberculosis. In this resistance pathway, the classical 4 → 3 cross-links are replaced by 3 → 3 cross-links, whose formation are catalyzed by the l,d-transpeptidases. To date, only one class of the entire β-lactam family, the carbapenems, is able to inhibit the l,d-transpeptidase activity. Nevertheless, the specificity of this inactivation is still not understood. Hence, the study of this new transpeptidase family is of considerable interest in order to understand the mechanism of the l,d-transpeptidases inhibition by carbapenems. In this context, we present herein the backbone and side-chain ¹H, ¹⁵N and ¹³C NMR assignment of the l,d-transpeptidase from Bacillus subtilis (Ldt_Bs) in the apo and in the acylated form with a carbapenem, the imipenem.     

Out-and-back 13C–13C scalar transfers in protein resonance assignment by proton-detected solid-state NMR under ultra-fast MAS

We present here ¹H-detected triple-resonance H/N/C experiments that incorporate CO–CA and CA–CB out-and-back scalar-transfer blocks optimized for robust resonance assignment in biosolids under ultra-fast magic-angle spinning (MAS). The first experiment, (H)(CO)CA(CO)NH, yields ¹H-detected inter-residue correlations, in which we record the chemical shifts of the CA spins in the first indirect dimension while during the scalar-transfer delays the coherences are present only on the longer-lived CO spins. The second experiment, (H)(CA)CB(CA)NH, correlates the side-chain CB chemical shifts with the NH of the same residue. These high sensitivity experiments are demonstrated on both fully-protonated and 100 %-H^N back-protonated perdeuterated microcrystalline samples of Acinetobacter phage 205 (AP205) capsids at 60 kHz MAS.     

Structure determination of proteins in <Superscript>2</Superscript>H<Subscript>2</Subscript>O solution aided by a deuterium-decoupled 3D HCA(N)CO experiment

We developed an NMR pulse sequence, 3D HCA(N)CO, to correlate the chemical shifts of protein backbone ¹Hα and ¹³Cα to those of ¹³C′ in the preceding residue. By applying ²H decoupling, the experiment was accomplished with high sensitivity comparable to that of HCA(CO)N. When combined with HCACO, HCAN and HCA(CO)N, the HCA(N)CO sequence allows the sequential assignment using backbone ¹³C′ and amide ¹⁵N chemical shifts without resort to backbone amide protons. This assignment strategy was demonstrated for ¹³C/¹⁵N-labeled GB1 dissolved in ²H₂O. The quality of the GB1 structure determined in ²H₂O was similar to that determined in H₂O in spite of significantly smaller number of NOE correlations. Thus this strategy enables the determination of protein structures in ²H₂O or H₂O at high pH values.     

Backbone <Superscript>1</Superscript>H, <Superscript>13</Superscript>C and <Superscript>15</Superscript>N chemical shift assignment of full-length human uracil DNA glycosylase UNG2

Human uracil N-glycosylase isoform 2—UNG2 consists of an N-terminal intrinsically disordered regulatory domain (UNG2 residues 1–92, 9.3 kDa) and a C-terminal structured catalytic domain (UNG2 residues 93–313, 25.1 kDa). Here, we report the backbone ¹H, ¹³C, and ¹⁵N chemical shift assignment as well as secondary structure analysis of the N-and C-terminal domains of UNG2 representing the full-length UNG2 protein.     

1H, 13C and 15N NMR assignments and secondary structure of the paramagnetic form of rat cytochrome b 5

Summary Modern multidimensional double- and triple-resonance NMR methods have been applied to assign the backbone and side-chain ¹³C resonances for both equilibrium conformers of the paramagnetic form of rat liver microsomal cytochrome b ₅. The assignment of backbone ¹³C resonances was used to confirm previous ¹H and ¹⁵N resonance assignments [Guiles, R.D. et al. (1993) Biochemistry, 32, 8329–8340]. On the basis of short- and medium-range NOEs and backbone ¹³C chemical shifts, the solution secondary structure of rat cytochrome b ₅ has been determined. The striking similarity of backbone ¹³C resonances for both equilibrium forms strongly suggests that the secondary structures of the two isomers are virtually identical. It has been found that the ¹³C chemical shifts of both backbone and side-chain atoms are relatively insensitive to paramagnetic effects. The reliability of such methods in anisotropic paramagnetic systems, where large pseudocontact shifts can be observed, is evaluated through calculations of the magnitude of such shifts.Abbreviations DANTE delays alternating with nutation for tailored excitation - DEAE diethylaminoethyl - DQF-COSY 2D double-quantum-filtered correlation spectroscopy - EDTA ethylenediaminetetraacetic acid - HCCH-TOCSY 3D proton-correlated carbon TOCSY experiment - HMQC 2D heteronuclear multiple-quantum correlation spectroscopy - HNCA 3D triple-resonance experiment correlating amide protons, amide nitrogens and alpha carbons - HNCO 3D triple-resonance experiment correlating amide protons, amide nitrogens and carbonyl carbons - HNCOCA 3D triple-resonance experiment correlating amide protons, amide nitrogens and alpha carbons via carbonyl carbons - HOHAHA 2D homonuclear Hartmann-Hahn spectroscopy - HOHAHA-HMQC 3D HOHAHA relayed HMQC - HSQC 2D heteronuclear single-quantum correlation spectroscopy - IPTG isopropyl thiogalactoside - NOESY 2D nuclear Overhauser enhancement spectroscopy - NOESY-HSQC 3D NOESY relayed HSQC - TOCSY 2D total correlation spectroscopy - TPPI time-proportional phase incrementation - TSP trimethyl silyl propionate     

Complete backbone and DENQ side chain NMR assignments in proteins from a single experiment: implications to structure–function studies

Resonance assignment is the first and the most crucial step in all nuclear magnetic resonance (NMR) investigations on structure–function relationships in biological macromolecules. Often, the assignment exercise has to be repeated several times when specific interactions with ligands, substrates etc., have to be elucidated for understanding the functional mechanisms. While the protein backbone serves to provide a scaffold, the side chains interact directly with the ligands. Such investigations will be greatly facilitated, if there are rapid methods for obtaining exhaustive information with minimum of NMR experimentation. In this context, we present here a pulse sequence which exploits the recently introduced technique of parallel detection of multiple nuclei, e.g. ¹H and ¹³C, and results in two 3D-data sets simultaneously. These yield complete backbone resonance assignment (¹H^N, ¹⁵N, ¹³CO, ¹Hα/¹³Cα, and ¹Hβ/¹³Cβ chemical shifts) and side chain assignment of D, E, N and Q residues. Such an exhaustive assignment has the potential of yielding accurate 3D structures using one or more of several algorithms which calculate structures of the molecules very reliably on the basis of NMR chemical shifts alone. The side chain assignments of D, E, N, and Q will be extremely valuable for interaction studies with different ligands; D and E side chains are known to be involved in majority of catalytic activities. Utility of this experiment has been demonstrated with Ca²⁺ bound M-crystallin, which contains largely D, E, N and Q residues at the metal binding sites.     

Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥90 % fraction of the residues, with an error rate smaller than ca 3.5 %, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (?, ψ) torsion angles of ca 12º. TALOS-N also reports sidechain χ¹ rotameric states for about 50 % of the residues, and a consistency with reference structures of 89 %. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts.     

Fast Assignment of <Superscript>15</Superscript>N-HSQC Peaks using High-Resolution 3D HNcocaNH Experiments with Non-Uniform Sampling

We describe an efficient NMR triple resonance approach for fast assignment of backbone amide resonance peaks in the ¹⁵N-HSQC spectrum. The exceptionally high resolutions achieved in the 3D HncocaNH and hNcocaNH experiments together with non-uniform sampling facilitate error-free sequential connection of backbone amides. Data required for the complete backbone amide assignment of the 56-residue protein GB1 domain were obtained in 14 h. Data analysis was vastly streamlined using a ‘backbone NH walk’ method to determine sequential connectivities without the need for ¹³C chemical shifts comparison. Amino acid residues in the sequentially connected NH chains are classified into two groups by a simple variation of the NMR pulse sequence, and the resulting ‘ZeBra’ stripe patterns are useful for mapping these chains to the protein sequence. In addition to resolving ambiguous assignments derived from conventional backbone experiments, this approach can be employed to rapidly assign small proteins or flexible regions in larger proteins, and to transfer assignments to mutant proteins or proteins in different ligand-binding states.     

CP-HISQC: a better version of HSQC experiment for intrinsically disordered proteins under physiological conditions

¹H–¹⁵N HSQC spectroscopy is a workhorse of protein NMR. However, under physiological conditions the quality of HSQC spectra tends to deteriorate due to fast solvent exchange. For globular proteins only a limited number of surface residues are affected, but in the case of intrinsically disordered proteins (IDPs) HSQC spectra are thoroughly degraded, suffering from both peak broadening and loss of intensity. To alleviate this problem, we make use of the following two concepts. (1) Proton-decoupled HSQC. Regular HSQC and its many variants record the evolution of multi-spin modes, 2N_xH_z or 2N_xH_x, in indirect dimension. Under the effect of fast solvent exchange these modes undergo rapid decay, which results in severe line-broadening. In contrast, proton-decoupled HSQC relies on N_x coherence which is essentially insensitive to the effects of solvent exchange. Moreover, for measurements involving IDPs at or near physiological temperature, N_x mode offers excellent relaxation properties, leading to very sharp resonances. (2) Cross-polarization ¹H-to-¹⁵N transfer. If CP element is designed such as to lock both ¹H^N and water magnetization, the following transfer is effected: $ {\text{H}}_{\text{x}}^{\text{water}} \to {\text{H}}_{\text{x}}^{\text{N}} \to {\text{N}}_{\text{x}} . $ Thus water magnetization is successfully exploited to boost the amount of signal. In addition, CP element suffers less loss from solvent exchange, conformational exchange, and dipolar relaxation compared to the more popular INEPT element. Combining these two concepts, we have implemented the experiment termed CP-HISQC (cross-polarization assisted heteronuclear in-phase single-quantum correlation). The pulse sequence has been designed such as to preserve water magnetization and therefore can be executed with reasonably short recycling delays. In the presence of fast solvent exchange, k_ex ~ 100 s^?1, CP-HISQC offers much better spectral resolution than conventional HSQC-type experiments. At the same time it offers up to twofold gain in sensitivity compared to plain proton-decoupled HSQC. The new sequence has been tested on the sample of drkN SH3 domain at pH 7.5, 30 °C. High-quality spectrum has been recorded in less than 1 h, containing resonances from both folded and unfolded species. High-quality spectra have also been obtained for arginine side-chain H^εN^ε groups in the sample of short peptide Sos. For Arg side chains, we have additionally implemented (HE)NE(CD)HD experiment. Using ¹³C-labeled sample of Sos, we have demonstrated that proton-to-nitrogen CP transfer remains highly efficient in the presence of solvent exchange as fast as k_ex = 620 s^?1. In contrast, INEPT transfer completely fails in this regime.     

Secondary structural analysis of proteins based on 13C chemical shift assignments in unresolved solid-state NMR spectra enhanced by fragmented structure database

Magic-angle-spinning solid-state ¹³C NMR spectroscopy is useful for structural analysis of non-crystalline proteins. However, the signal assignments and structural analysis are often hampered by the signal overlaps primarily due to minor structural heterogeneities, especially for uniformly-¹³C,¹⁵N labeled samples. To overcome this problem, we present a method for assigning ¹³C chemical shifts and secondary structures from unresolved two-dimensional ¹³C–¹³C MAS NMR spectra by spectral fitting, named reconstruction of spectra using protein local structures (RESPLS). The spectral fitting was conducted using databases of protein fragmented structures related to ¹³C^α, ¹³C^β, and ¹³C′ chemical shifts and cross-peak intensities. The experimental ¹³C–¹³C inter- and intra-residue correlation spectra of uniformly isotope-labeled ubiquitin in the lyophilized state had a few broad peaks. The fitting analysis for these spectra provided sequence-specific C^α, C^β, and C′ chemical shifts with an accuracy of about 1.5 ppm, which enabled the assignment of the secondary structures with an accuracy of 79 %. The structural heterogeneity of the lyophilized ubiquitin is revealed from the results. Test of RESPLS analysis for simulated spectra of five different types of proteins indicated that the method allowed the secondary structure determination with accuracy of about 80 % for the 50–200 residue proteins. These results demonstrate that the RESPLS approach expands the applicability of the NMR to non-crystalline proteins exhibiting unresolved ¹³C NMR spectra, such as lyophilized proteins, amyloids, membrane proteins and proteins in living cells.     

Stable carbon and nitrogen isotope ratios of Eucalyptus and Acacia species along a seasonal rainfall gradient in Western Australia

Key message

Eucalyptus and Acacia species were surprisingly similar with respect to variations in δ ¹³ C, δ ¹⁵ N. Both genera respond with speciation and associated changes in leaf structure to drought.

Abstract

Stable carbon and nitrogen isotope ratios (δ¹³C and δ¹⁵N) in leaves of eucalypts (Corymbia and Eucalyptus) and Acacia (and some additional Fabaceae) species were investigated together with specific leaf area (SLA), leaf nitrogen (N) and leaf phosphorous (P) concentration along a north–south transect through Western Australia covering winter- and summer-dominated rainfall between 100 and 1,200 mm annually. We investigated 62 eucalypts and 78 woody Fabaceae species, mainly of the genus Acacia. Leaf δ¹³C values of Eucalyptus and Acacia species generally increased linearly with latitude from ?29.5 ± 1.3 ‰ in the summer-dominated rainfall zone (15°S–18°S) to about ?25.7 ± 1.1 ‰ in the winter-dominated rainfall zone (29°S–31°S). δ¹⁵N increased initially with southern latitudes (0.5 ± 1.6 ‰ at 15°S; 5.8 ± 3.3 ‰ at 24–29°S) but decreased again further South (4.6 ± 3.5 ‰ at 31°S). The variation in δ¹³C and δ¹⁵N was probably due to speciation of Eucalyptus and Acacia into very local populations. There were no species that were distributed over the whole sampling area. The variation in leaf traits was larger between species than within species. Average nitrogen concentrations were 11.9 ± 1.05 mg g^?1 in Eucalyptus, and were 18.7 ± 4.1 mg g^?1 in Acacia. Even though the average nitrogen concentration was higher in Acacia than Eucalyptus, δ¹⁵N gave no clear indication for N₂ fixation in Acacia. In a multiple regression, latitude (as a surrogate for rainfall seasonality), mean rainfall, leaf nitrogen concentration, specific leaf area and nitrogen fixation were significant and explained 69 % of the variation of δ¹³C, but only 36 % of the variation of δ¹⁵N. Higher nitrogen and phosphorus concentration could give Acacia an advantage over Eucalyptus in arid regions of undefined rainfall seasonality.