Clustering on the relative abundances of different amino acid residues reveals a clear segregation of the halophilic organisms from the non-halophiles (Figure 1). The left panel of Figure 1 depicts the unweighted pair group average clustering on the relative abundances of different amino acid residues in the encoded proteins of the 6 extreme halophilic and 24 non-halophilic organisms under study (Table 1) with respect to those of Escherichia coli, while the right panel offers a pictorial representation of relative amino acid usage in the respective organisms. As the relative abundances of the residues increase from 0.35 to 1.80, the color of the respective block changes from red to green, that is, the greener the color, the more abundant is the residue in that organism compared to E. coli. Halophilic organisms show quite distinct usage of amino acid residues compared to non-halophiles, elucidated by the presence of either more red or green blocks in Figure 1. Among the prominent trends are significant increases in Asp, Glu, Val, and Thr residues and decreases in Lys, Met, Leu, Ile, and Cys in halophilic proteomes. Usage of Ile is lower in all halophiles except H. walsbyi, probably due to its significantly lower genomic GC-content (Table 1). The increase in negatively charged (Asp and Glu) and Thr residues and the decrease in Lys and strong hydrophobic residues (Ile, Met, Leu) are consistent with earlier reports 412141822. A relatively higher frequency of Val in extreme halophiles compared to non-halophiles supports the observation of Madern et al. 15, but contradicts earlier propositions on under-representation of all strong hydrophobic residues in halophiles 423.

Similar to the cluster analysis, correspondence analysis (COA) on amino acid usage also segregates the halophilic organisms from the non-halophiles along the second principal axis (Figure 2a). The first two principal axes of the COA contribute 16.29% and 13.79%, respectively, to the total variability. A strong negative correlation (r² = 0.57, p < 10^-7) of axis 1 with the GC-content of the respective genomes identifies GC-bias as one of the major sources of inter-species variation in global amino acid composition, while the contributions to axis 2 come from hydrophobicity (negative correlation, with r² = 0.65, p < 10^-7) and the ratio of negatively versus positively charged amino acid residues (positive correlation, with r² = 0.26, p < 10^-7) of the encoded gene products of the organisms. This indicates, therefore, that the proteins of halophilic organisms are characterized by less hydrophobicity (or higher hydrophilicity) and relatively higher usage of negatively charged amino acids compared to non-halophile proteins. Figure 2b, c also supports the corollary that the features of halophilic proteomes are unique and quite distinct from those of non-halophiles with respect to hydrophobicity and usage of negatively charged amino acids (as predicted by isoelectric point distribution of encoded proteins).

All these trends are specifically exhibited by halophiles irrespective of their taxonomic origins and their genomic GC-content (Additional data file 1 and Table 1). For instance, five archaeal halophiles appear in a distinct cluster, far away from other closely related archaeal species like Methanosaeta thermophila, Thermoplasma acidophilum and so on (Figure 1). The salt-adapted bacteroidetes/chlorobi Salinibacter ruber also intermingles with these halophilic archaea - wide apart from Pelodictyon luteolum, its closest non-halophilic taxonomic relative. H. walsbyi, a halophile with relatively low GC-content (47.9%), appears in the same cluster along with the GC-rich halophiles, while the three non-halophilic species with similar GC-content and (E. coli, 50%; Shigella boydii 47.4%; and Yersinia pestis, 47.8%) cluster with the other non-halophiles, most of which are characterized by much higher GC-content. It is worth mentioning at this point that organisms with high growth temperature also cluster together (Figure 1), of which two methanogenic organisms (M. thermophila and Methanothermobacter thermautotrophicus) share the same node. The distinct branching pattern of three thermophiles with relatively low genomic GC-content (T. acidophilum, Thermotoga maritima and Thermococcus kodakarensis) suggests that the overall GC-content also plays a significant role in shaping the amino acid composition of such organisms, as observed previously by Kreil and Ouzounis 24. The exact topology of the cluster and values indicated by the colored blocks depend on the choice of standardization and the algorithm used for their construction, but the resulting grouping of the organisms in Figure 1 does not change significantly from that obtained using actual amino acid compositions of the respective organisms. These observations point towards convergent evolution of halophilic proteomes for specific amino acid composition, despite their varying GC-bias and widely disparate taxonomic positions.

A comparison of orthologous proteins (cytosolic and membrane proteins separately) between halophilic and non-halophilic organisms was performed to identify the underlying factors for halophilic adaptation in more detail. Table 2 summarizes different proteomic properties of four sets of orthologous cytosolic proteins between halophiles and non-halophiles. In all cases, there is a significant increase in negatively charged, hydrophobic (Val) and borderline hydrophobic (Thr) residues and a decrease in positively charged, large hydrophobic and Cys residues (Table 2). Among negatively charged residues, the abundance of Asp (44% for set I, 65% for set II, 69% for set III and 55% for set IV) is higher than that of Glu (16% for set I, 43% for set II, 26% for set III and 34% for set IV). Similar trends were observed for the membrane proteins, although fairly large differences in amino acid usage were not found (data not shown).

We determined the frequencies of all possible amino acid replacements (that is, (20 × 19)/2 = 190 possible pairs of replacements) between the orthologous sequences in the direction from non-halophile to halophile proteins (Additional data files 2-5). There are 59 (31% of all possible pairs), 51 (26% of all possible pairs), 81 (42% of all possible pairs) and 76 (40% of all possible pairs) pairs of amino acids for sets I, II, III and IV, respectively, that have significant directional replacement bias (p < 10^-2 for set II; p < 10^-3 for set I; and p < 10^-6 for sets III and IV). They contribute 56%, 52%, 66% and 63% of the replacements for set I (28,267 of the 50,403 observed replacements), set II (10,815 of the 20,685 observed replacements), set III (69,974 of the 105,771 observed replacements) and set IV (68,243 of the 107,474 observed replacements), respectively (Additional data files 6-9). The top 20 replacements in all these sets suggest that there are two clear trends in amino acid substitution patterns in terms of highest gain as well as highest ratio (Table 3). These are: Lys (non-halophile) substituted by other residues (halophile); and other residues (non-halophile) substituted by acidic residues, especially Asp (halophile). Lys→Asp topped the list of most significantly biased substitutions in terms of ratio in all the sets under study, indicating that this trend is independent of GC-composition and phylogeny. Another notable trend is Ile/Leu (non-halophile) substituted by Val/other residues (halophile). In set II, where the orthologs are of similar GC-composition, there is a prevalence of overall gain in Asp, Glu, Val and Thr, which are also gained in sets I, III and IV in halophile from non-halophile orthologs (Table 3). Thus, there is a prevalence of overall gain in Asp, Glu, Val and Thr and the most prominent losses common in all four groups are Lys, Ile, Met, Leu and Cys in halophile from non-halophile orthologs. This result suggests that such gains and losses indeed represent an imprint of halophilic adaptation, and not the dragging effect of mutational bias or taxonomic differences.