1. Genomic constitution of Neisseria is multi-factorial and complex
The GC/AT content of organisms is one of the most highly variable traits (Botzman and Margalit, 2011). Variation in nucleotides can be observed in protein coding genes, non-protein coding genes, synonymous sites as well as non-synonymous sites of genomes (Reis et al. 2004). The genomic constitution of Neisseria revealed that this genus is neither GC biased nor AT biased. Previously it has been reported that, mutational biases determine the nucleotide composition which means GC biased mutation pattern resulted in GC rich organisms and AT biased mutation developed AT rich organisms (Hershberg and Petrov, 2010). However, recently the in-effectivity of mutational bias in directing the nucleotide composition has been revealed. This happens in organisms which are both AT and GC rich (Hildebrand et al. 2010). This also happened in the case of Neisseria. In such organisms, mutations are more likely to happen from G/C towards A/T due to the rapid deamination of cytosine to thymine (C > T/U) (Bohlin et al. 2017). However, increased AT content indicates genomic disability (Yakovchuk et al. 2006). In such situations, another selectively neutral pressure termed as ‘amelioration’ acts as a major force which even out the differences in base composition (Lawrence and Ochman, 1997). Such cases are beneficial for pathogens with an AT rich host (human for our case) (Bohlin 2011). Thus, the genomic organization of Neisseria does not directly depend solely upon its nucleotide variation. Instead, it is a multi-factorial process that is resulted through a complex combination of both neutral and selective processes. This was also validated by the significantly negative correlation (r= -0.67; p< 0.01) between ENc and CAI. The value of ENc ranges from 20-62 and a negative correlation between ENc and CAI indicates the pivotal roles of codon usage indices other than compositional constraint. To determine those factors, we used the Spearman rank correlation method. A positive correlation (r=0.86; p<0.001) between CAI and C3 was observed among all select strains. Preference towards Cytosine (C) in AT/GC unbiased organisms further strengthens the role of mutational pressure on these genomes. The third position of the codon is a hotspot for random mutation without a drastic effect on amino acid usage due to the redundancy of codons. Thus, it can be posulated that, deamination of C to Uracil (U) in Neisseria not only increases the AT richness of the genome but also helps this genus to aptly use the host translational machinery using the human tRNA pool. The presence of active cytidine deaminase responsible for C>U mutation has been reported in pathogens like E. coli and S. typhimurium (Henderson and Paterson, 2014). Such activity may also be present in Neisseria with a pivotal role in their genomic constituency. This arrangement of codon usage indices was found to be consistent among the secretomes and pathogenicity related genes present in Neisseria. Moreover, no significant difference was found in this pattern between the pathogenic and non-pathogenic Neisseria strains.
2. Optimal codons are mounting the quantity of energy economic amino acids in Neisseria
Another factor found to play an important role in Neisseria genomes was Fop. A positive correlation between CAI and Fop (r= 0.84, p<0.001) supported the previous statement. This value indicated higher usage of optimal codons in potentially highly expressed genes than lowly expressed genes. Twenty-nine codons were found to be optimal codons. Among them nineteen were GC rich codons and fifteen ended with Cytosine (C). This leads to an important aspect regarding the amino acid usage of select genomes. GC rich codons code for more energy economic amino acids rather than AT rich codons (Bohlin et al. 2017). Thus, the higher usage of such GC rich optimal codons in PHX genes indicated less biosynthetic energy cost for respective translated proteins. To further assess these findings the correlation between PEC, CAI and Fop was calculated for both PHX and PLX. A positive correlation between CAI and Fop (r= 0.84, p<0.001) along with negative correlation among PEC and CAI (r= -0.76, p<0.001) as well as Fop and PEC (r=-0.68, p<0.001) was obtained for PHX proteins. On the contrary, positive correlation was found between Fop and PEC (r=0.34, p<0.01) as well as CAI and PEC (r=0.36, p<0.01). This result indicated that, although the Neisseria genomes are not generally biased towards either AT or GC rich codons (Fig. 1a), natural selection is discriminating among the synonymous codons and preferring GC rich codons in PHX genes. This enhances the translational elongation rates as well as reduces misincorporation of amino acids during protein synthesis (Akashi and Gojobori, 2002). Previously, Akashi and Gojobori (2002) reported a relation between the protein energy cost (PEC) and tRNA adaptation in differentially expressed genes. Hence, we correlated PEC and tAI. We found a negative correlation (r=-0.75, p<0.001) between them among PHX. This further validated the translational efficiency of potentially highly expressed genes along with an indication that afterwards these genes will be translated into energy economic proteins with higher expression level. An overall amino acid usage (Fig. 1b) calculation indicated alanine, valine, glycine, serine, asparagine, proline, glutamic acids and threonine were highly used in Neisseria. The overall usage of costly aromatic amino acids like phenylalanine, tyrosine and tryptophan were comparatively lower than the aforementioned amino acids. No significant difference was found in this pattern between the pathogenic and commensal Neisseria strains.
3. RSCU pattern indicated towards co-evolution Neisseria for better host adaptation
Previous studies have shown the relation between codon adaptation and ecological preferences (Peden 1998). A relation between the codon adaptation and co-evolution has also been drawn. To assess the co-evolutionary pattern between Neisseria and their host Homo sapiens, their RSCU pattern was exploited. We found fourteen codons (ATC, TAC, TTC, GCC, CTG, TCC, TGC, CAC, AAC, ACC, GGC, GTC, CCC, GAC) were optimally used in both Neisseria and human. Moreover, ~96% pathogenic island genes in Neisseria were under the PHX category. This suggested elevated translational efficiency of those genes in the host body. The translational selection pressure towards these fourteen most adapted codons aided the microbes to live in the host environment and efficiently utilize their metabolic resources (Botzman and Margalit, 2011). Thus, the codon usage is playing a pivotal role in enhancing the cellular fitness of Neisseria within the host body mostly by mimicking the codon usage pattern of humans.
4. Co-existence of Neisseria with human host
The genus Neisseria composed of both pathogenic and non-pathogenic commensal bacteria. According to the ecological principles, co-existence can be ruled either via competition or complementation (Carr and Borenstein 2012; Levy and Borenstein 2012). The reverse ecology analysis among select Neisseria and their host (human) revealed inter-species specific and intra-species-specific competition among members of Neisseria (Fig. 2a, 2b). The pathogenic strains were exerting more competition on commensal strains. Both types of strains were found to exert a moderate competition against humans dictating an efficient distribution of host-derived resources among pathogenic and commensal Neisseria (Fig. 2a). However, the competition exerted by humans on Neisseria was diminutive. This has turned humans into the perfect host for this microbial genus.
The complementation indices among considered microbes were found to be very low. Thus, co-existence of different Neisseria strains in a small niche can be least expected. This also explains the broad range of distribution (for example, brain, oral cavity, respiratory system, reproductive system, urinary tract etc.) of Neisseria within the human body. However, all select strains showed complementation (0.26-0.44) with humans. This metabolic reconstruction clearly (Fig. 2c) depicted that, large number of resources are shared and utilized efficiently between humans and Neisseria. This suggested the co-inhabitation of Neisseria within the human body is ecologically favorable.
5. Differential evolutionary pattern indicated transition from commensalism to pathogenicity among Neisseria
The rate of evolution among protein coding genes varies tremendously. Evolutionary analysis based upon ka/ks (or ω) value revealed a differential decoration among diverse sets of genes. It was found that PHX genes were less evolved (p<0.001) and more conserved than PLX genes. The ‘knock-out rate’ prediction proposed that most of the PHX genes are essential or housekeeping genes with important functionality (Hust and Smith, 1999). These essential genes evolve more slowly than other non-essential genes (Wilson et al. 1977). Similar results were also found previously in Escherichia coli, Helicobacter pylori and even in Neisseria meningitis (Jordan et al. 2002). Moreover, secretomes of pathogens continuously struggle with the host immune system and try to beat it which resulted in their faster evolution (Ehrlich et al. 2008; Saha et al. 2019). This differential evolutionary pattern for pathogens indicated the possibility for emergence of pathogenicity from commensalism among Neisseria.
Another aspect of our ka/ks analysis was based on pathogenicity related (PI) genes. We found a set of pathogenic genes were present in non-pathogenic Neisseria strains which was unexpected. Few studies (Calder et al. 2020; Lu et al. 2019; Clemence et al. 2018) on Neisseria have also reported these surprising results where the potent virulent genes of N. meningitis and N. gonorrhea were found in nonpathogenic N. lactemia (Snyder and Saunders, 2006). However, no clear explanation for this result is still stated. Hence, we calculated the evolutionary rates of PI genes from both pathogenic and non-pathogenic strains to reveal whether a transition from pathogenicity to commensalism has occurred during evolution of Neisseria or vice-versa. The PI genes were highly (p<0.001) evolved in pathogenic strains rather than their nonpathogenic counterparts. The ω value of pathogenic PI genes ranged from 0.32-0.45 whereas the same for non-pathogenic strains ranged from 0.05-0.08. Their difference was statistically significant (p<0.001). Hence the transition from commensalism to pathogenicity in Neisseria is evident from this result. This type of transition was previously reported in Mycobacterium avium complex (Saha et al. 2019). Moreover, nine protein coding genes have been reported to be associated with antimicrobial resistance for N. gonorrhea. Orthologs of those genes were found in all considered strains. Evolution analysis among them predicted their higher evolution in pathogens rather than nonpathogens. The mean ka/ks value for each of the nine genes were lowest when only non-pathogenic strains were studied. The rate of evolution increased when we considered both pathogen and non-pathogens (strains from cluster III from pan-genomic dendrogram) together and the value was highest after only pathogens were considered (Fig. 4).
This supported our aforementioned hypothesis for transition from commensalism to pathogenicity among Neisseria. With the emergence of pathogenicity this genus became exposed to both narrow- as well as broad-spectrum antibiotics and in the long run their anti-microbial resistance property evolved.
6. PPI study of Neisseria-Human interaction
Protein-protein interaction (PPI) analysis has become a major tool in system biology with its ability to handle a broad range of data related to biological processes, cell signaling and developmental strategies (Rao et al. 2014). In this study we have studied the PPI network among N. gonorrhea (N_gon), N. meningitis (N_men) and Homo sapiens. The PI protein related PPI network of considered pathogenic strains have been given in Fig. 5a and 5b. The COG based clustering of both the networks showed “cellular processing and signaling” category (red circle) contained most connected proteins. Those proteins were also connected with others associated with “information storage and processing” (yellow circles) and “Metabolism” (blue circles) categories. Few proteins (crimson circles) were proteins with uncharacterized COG category and their connectedness was less than other proteins. Overall, the PPI score was 1.0e-16. Similar pattern of clustering was observed for NM where the pink circles were protein for “cellular processing and signaling”, green circles were for “information storage and processing”, yellow circles were for “Metabolism” and red circles were unknown categories. The PPI enrichment score for N. meningitis was 1.0e-15. These values for both the PPI networks indicated a stable and promising interaction among the pathogenic proteins.
Another aspect of this study was to analyze the human-Neisseria interaction. The human PPI network associated with Gonorrhea and Meningitis were predicted. A huge number of proteins with tight inter-connection were found to be linked directly or indirectly with both these disorders. Twenty human proteins were found to be directly associated with Gonorrhea having DSI (disease-significant index) more than 0.7. Their KEGG enrichment analysis revealed their functionality with oocyte meiosis, cell cycle, Epstein-Barr virus infection, dopaminergic synapse, acrosomal vesicle formation, Hippo signaling pathway, long-term depression, sphingolipid signaling pathway, p53 signaling pathway, FoxO signaling pathway and autophagy (Fig. 5c). Ten potent human proteins were found to be directly related to Meningitis with DSI value more than 7. KEGG enrichment of those proteins revealed their pivotal role in tryptophan metabolism, prion diseases, complement and coagulation cascades, Systemic lupus erythematosus (SLE), Seleno-compound metabolism, amoebiasis and axon development (Fig. 5d). The PPI analysis among NG and human revealed acrosomal vesicle formation, Hippo signaling pathway, Epstein-Barr virus infection, long-term depression and p53 signaling pathway related proteins interacted with NG PI proteins with P-value 1.0e-16. NG causing Gonorrhea, a sexually transmitted disorder (STD) is thus interacting with human proteins that are directly related to the development of urogenital tract, oocyte meiosis, placenta and sperm formation and development (Soncin and Parast 2020; Caini et al. 2014). The same analysis with NM and human proteins revealed a strong biological interaction (P-value 1.0e-16) between NM PI protein and human proteins related to prion diseases, axon development, tryptophan metabolism, SLE and blood brain barrier formation. Clinical reports have been found that patients with SLE and prion diseases are more prone to Meningitis (Al Mahmeed et al. 2020; Batra et al. 2016). Thus, the PPI network analysis further established the complex machinery of Human-Neisseria interaction.