Evidence for Host-Bacterial Co-evolution via Genome Sequence Analysis of 480 Thai Mycobacterium tuberculosis Lineage 1 Isolates.

Tuberculosis presents a global health challenge. Mycobacterium tuberculosis is divided into several lineages, each with a different geographical distribution. M. tuberculosis lineage 1 (L1) is common in the high-burden areas in East Africa and Southeast Asia. Although the founder effect contributes significantly to the phylogeographic profile, co-evolution between the host and M. tuberculosis may also play a role. Here, we reported the genomic analysis of 480 L1 isolates from patients in northern Thailand. The studied bacterial population was genetically diverse, allowing the identification of a total of 18 sublineages distributed into three major clades. The majority of isolates belonged to L1.1 followed by L1.2.1 and L1.2.2. Comparison of the single nucleotide variant (SNV) phylogenetic tree and the clades defined by spoligotyping revealed some monophyletic clades representing EAI2_MNL, EAI2_NTM and EAI6_BGD1 spoligotypes. Our work demonstrates that ambiguity in spoligotype assignment could be partially resolved if the entire DR region is investigated. Using the information to map L1 diversity across Southeast Asia highlighted differences in the dominant strain-types in each individual country, despite extensive interactions between populations over time. This finding supported the hypothesis that there is co-evolution between the bacteria and the host, and have implications for tuberculosis disease control

A novel Ancestral Beijing sublineage of Mycobacterium tuberculosis suggests the transition site to Modern Beijing sublineages.

Global Mycobacterium tuberculosis population comprises 7 major lineages. The Beijing strains, particularly the ones classified as Modern groups, have been found worldwide, frequently associated with drug resistance, younger ages, outbreaks and appear to be expanding. Here, we report analysis of whole genome sequences of 1170 M. tuberculosis isolates together with their patient profiles. Our samples belonged to Lineage 1-4 (L1-L4) with those of L1 and L2 being equally dominant. Phylogenetic analysis revealed several new or rare sublineages. Differential associations between sublineages of M. tuberculosis and patient profiles, including ages, ethnicity, HIV (human immunodeficiency virus) infection and drug resistance were demonstrated. The Ancestral Beijing strains and some sublineages of L4 were associated with ethnic minorities while L1 was more common in Thais. L2.2.1.Ancestral 4 surprisingly had a mutation that is typical of the Modern Beijing sublineages and was common in Akha and Lahu tribes who have migrated from Southern China in the last century. This may indicate that the evolutionary transition from the Ancestral to Modern Beijing sublineages might be gradual and occur in Southern China, where the presence of multiple ethnic groups might have allowed for the circulations of various co-evolving sublineages which ultimately lead to the emergence of the Modern Beijing strains

Mine the Gaps : Evolution of Eukaryotic Protein Indels and their Application for Testing Deep Phylogeny

Insertions/deletions (indels) are potentially powerful evolutionary markers, but little is known about their evolution and few tools exist to effectively study them. To address this, I developed SeqFIRE, a tool for automated identification and extraction of indels from protein multiple sequence alignments. The program also extracts conserved alignment blocks, thus covering all major steps in preparing multiple sequence alignments for phylogenetic analysis. I then used SeqFIRE to build an indel database, using 299 single copy proteins from a broad taxonomic sampling of mainly multicellular eukaryotes. A total of 4,707 indels were extracted, of which 901 are simple (one genetic event) and 3,806 are complex (multiple events). The most abundant indels are single amino acid simple indels. Indel frequency decreases exponentially with length and shows a linear relationship with host protein size. Singleton indels reveal a strong bias towards insertions (2.31 x deletions on average). These analyses also identify 43 indels marking major clades in Plantae and Fungi (clade defining indels or CDIs), but none for Metazoa. In order to study the 3806 complex indels they were first classified by number of states. Analysis of the 2-state complex and simple indels combined (“bi-state indels”) confirms that insertions are over 2.5 times as frequent as deletions. Three-quarters of the complex indels had three-nine states (“slightly complex indels”). A tree-assisted search method was developed allowing me to identify 1,010 potential CDIs supporting all examined major branches of Plantae and Fungi. Forty-two proteins were also found to host complex indel CDIs for the deepest branches of Metazoa. After expanding the taxon set for these proteins, I identified a total of 49 non-bilaterian specific CDIs. Parsimony analysis of these indels places Ctenophora as sister taxon to all other Metazoa including Porifera. Six CDIs were also found placing Placozoa as sister to Bilateria. I conclude that slightly complex indels are a rich source of CDIs, and my tree-assisted search strategy could be automated and implemented in the program SeqFIRE to facilitate their discovery. This will have important implications for mining the phylogenomic content of the vast resource of protist genome data soon to become available

Mine the Gaps : Evolution of Eukaryotic Protein Indels and their Application for Testing Deep Phylogeny

Insertions/deletions (indels) are potentially powerful evolutionary markers, but little is known about their evolution and few tools exist to effectively study them. To address this, I developed SeqFIRE, a tool for automated identification and extraction of indels from protein multiple sequence alignments. The program also extracts conserved alignment blocks, thus covering all major steps in preparing multiple sequence alignments for phylogenetic analysis. I then used SeqFIRE to build an indel database, using 299 single copy proteins from a broad taxonomic sampling of mainly multicellular eukaryotes. A total of 4,707 indels were extracted, of which 901 are simple (one genetic event) and 3,806 are complex (multiple events). The most abundant indels are single amino acid simple indels. Indel frequency decreases exponentially with length and shows a linear relationship with host protein size. Singleton indels reveal a strong bias towards insertions (2.31 x deletions on average). These analyses also identify 43 indels marking major clades in Plantae and Fungi (clade defining indels or CDIs), but none for Metazoa. In order to study the 3806 complex indels they were first classified by number of states. Analysis of the 2-state complex and simple indels combined (“bi-state indels”) confirms that insertions are over 2.5 times as frequent as deletions. Three-quarters of the complex indels had three-nine states (“slightly complex indels”). A tree-assisted search method was developed allowing me to identify 1,010 potential CDIs supporting all examined major branches of Plantae and Fungi. Forty-two proteins were also found to host complex indel CDIs for the deepest branches of Metazoa. After expanding the taxon set for these proteins, I identified a total of 49 non-bilaterian specific CDIs. Parsimony analysis of these indels places Ctenophora as sister taxon to all other Metazoa including Porifera. Six CDIs were also found placing Placozoa as sister to Bilateria. I conclude that slightly complex indels are a rich source of CDIs, and my tree-assisted search strategy could be automated and implemented in the program SeqFIRE to facilitate their discovery. This will have important implications for mining the phylogenomic content of the vast resource of protist genome data soon to become available

Mine the Gaps : Evolution of Eukaryotic Protein Indels and their Application for Testing Deep Phylogeny

Insertions/deletions (indels) are potentially powerful evolutionary markers, but little is known about their evolution and few tools exist to effectively study them. To address this, I developed SeqFIRE, a tool for automated identification and extraction of indels from protein multiple sequence alignments. The program also extracts conserved alignment blocks, thus covering all major steps in preparing multiple sequence alignments for phylogenetic analysis. I then used SeqFIRE to build an indel database, using 299 single copy proteins from a broad taxonomic sampling of mainly multicellular eukaryotes. A total of 4,707 indels were extracted, of which 901 are simple (one genetic event) and 3,806 are complex (multiple events). The most abundant indels are single amino acid simple indels. Indel frequency decreases exponentially with length and shows a linear relationship with host protein size. Singleton indels reveal a strong bias towards insertions (2.31 x deletions on average). These analyses also identify 43 indels marking major clades in Plantae and Fungi (clade defining indels or CDIs), but none for Metazoa. In order to study the 3806 complex indels they were first classified by number of states. Analysis of the 2-state complex and simple indels combined (“bi-state indels”) confirms that insertions are over 2.5 times as frequent as deletions. Three-quarters of the complex indels had three-nine states (“slightly complex indels”). A tree-assisted search method was developed allowing me to identify 1,010 potential CDIs supporting all examined major branches of Plantae and Fungi. Forty-two proteins were also found to host complex indel CDIs for the deepest branches of Metazoa. After expanding the taxon set for these proteins, I identified a total of 49 non-bilaterian specific CDIs. Parsimony analysis of these indels places Ctenophora as sister taxon to all other Metazoa including Porifera. Six CDIs were also found placing Placozoa as sister to Bilateria. I conclude that slightly complex indels are a rich source of CDIs, and my tree-assisted search strategy could be automated and implemented in the program SeqFIRE to facilitate their discovery. This will have important implications for mining the phylogenomic content of the vast resource of protist genome data soon to become available

Evolution of protein indels in plants, animals and fungi

Background: Insertions/deletions (indels) in protein sequences are useful as drug targets, protein structure predictors, species diagnostics and evolutionary markers. However there is limited understanding of indel evolutionary patterns. We sought to characterize indel patterns focusing first on the major groups of multicellular eukaryotes. Results: Comparisons of complete proteomes from a taxonically broad set of primarily Metazoa, Fungi and Viridiplantae yielded 299 substantial (>250aa) universal, single-copy (in-paralog only) proteins, from which 901 simple (present/absent) and 3,806 complex (multistate) indels were extracted. Simple indels are mostly small (1-7aa) with a most frequent size class of 1aa. However, even these simple looking indels show a surprisingly high level of hidden homoplasy (multiple independent origins). Among the apparently homoplasy-free simple indels, we identify 69 potential clade-defining indels (CDIs) that may warrant closer examination. CDIs show a very uneven taxonomic distribution among Viridiplante (13 CDIs), Fungi (40 CDIs), and Metazoa (0 CDIs). An examination of singleton indels shows an excess of insertions over deletions in nearly all examined taxa. This excess averages 2.31 overall, with a maximum observed value of 7.5 fold. Conclusions: We find considerable potential for identifying taxon-marker indels using an automated pipeline. However, it appears that simple indels in universal proteins are too rare and homoplasy-rich to be used for pure indel-based phylogeny. The excess of insertions over deletions seen in nearly every genome and major group examined maybe useful in defining more realistic gap penalties for sequence alignment. This bias also suggests that insertions in highly conserved proteins experience less purifying selection than do deletions

Evolution of protein indels in plants, animals and fungi

Background: Insertions/deletions (indels) in protein sequences are useful as drug targets, protein structure predictors, species diagnostics and evolutionary markers. However there is limited understanding of indel evolutionary patterns. We sought to characterize indel patterns focusing first on the major groups of multicellular eukaryotes. Results: Comparisons of complete proteomes from a taxonically broad set of primarily Metazoa, Fungi and Viridiplantae yielded 299 substantial (>250aa) universal, single-copy (in-paralog only) proteins, from which 901 simple (present/absent) and 3,806 complex (multistate) indels were extracted. Simple indels are mostly small (1-7aa) with a most frequent size class of 1aa. However, even these simple looking indels show a surprisingly high level of hidden homoplasy (multiple independent origins). Among the apparently homoplasy-free simple indels, we identify 69 potential clade-defining indels (CDIs) that may warrant closer examination. CDIs show a very uneven taxonomic distribution among Viridiplante (13 CDIs), Fungi (40 CDIs), and Metazoa (0 CDIs). An examination of singleton indels shows an excess of insertions over deletions in nearly all examined taxa. This excess averages 2.31 overall, with a maximum observed value of 7.5 fold. Conclusions: We find considerable potential for identifying taxon-marker indels using an automated pipeline. However, it appears that simple indels in universal proteins are too rare and homoplasy-rich to be used for pure indel-based phylogeny. The excess of insertions over deletions seen in nearly every genome and major group examined maybe useful in defining more realistic gap penalties for sequence alignment. This bias also suggests that insertions in highly conserved proteins experience less purifying selection than do deletions

SeqFIRE : a web application for automated extraction of indel regions and conserved blocks from protein multiple sequence alignments

Analyses of multiple sequence alignments generally focus on well-defined conserved sequence blocks, while the rest of the alignment is largely ignored or discarded. This is especially true in phylogenomics, where large multigene datasets are produced through automated pipelines. However, some of the most powerful phylogenetic markers have been found in the variable length regions of multiple alignments, particularly insertions/deletions (indels) in protein sequences. We have developed Sequence Feature and Indel Region Extractor (SeqFIRE) to enable the automated identification and extraction of indels from protein sequence alignments. The program can also extract conserved blocks and identify fast evolving sites using a combination of conservation and entropy. All major variables can be adjusted by the user, allowing them to identify the sets of variables most suited to a particular analysis or dataset. Thus, all major tasks in preparing an alignment for further analysis are combined in a single flexible and user-friendly program. The output includes a numbered list of indels, alignments in NEXUS format with indels annotated or removed and indel-only matrices. SeqFIRE is a user-friendly web application, freely available online at www.seqfire.org/

Infection of multiple Mycobacterium tuberculosis strains among tuberculosis/human immunodeficiency virus co-infected patients: A molecular study in Myanmar

Background: Appearance of Mycobacterium tuberculosis (MTB) in the sputum of a tuberculosis (TB)/human immunodeficiency virus (HIV) co-infected patient under treatment may indicate either failure or new infection. This study aims to evaluate whether TB treatment failure among TB/HIV co-infected patients is a real failure. Methods: A prospective cohort study was conducted among 566 TB/HIV co-infected patients who started TB treatment in 12 townships in the upper Myanmar. Among the 566 participants, 16 (2.8%) resulted in treatment failure. We performed a molecular study using mycobacterial interspersed repetitive-unit-variable number of tandem repeat (MIRU-VNTR) genotyping for them. The MIRU-VNTR profiles were analyzed using the web server, MIRU-VNTRplus. All data were entered into EpiData version 3.1 and analyzed using R version 3.4.3. Results: Among 16 failure patients, seven had incomplete laboratory results. Of the nine remaining patients, nobody had exactly the same MIRU-VNTR pattern between the initial and final isolates. Four patients had persistent East-African Indian (EAI) lineages and one each had persistent Beijing lineage, changing from EAI to Beijing, from Beijing to EAI, NEW-1 to Beijing, and NEW-1 to X strains. Female patients have significantly larger genetic difference between MTB of the paired isolates than male patients (t-test, P = 0.04). Conclusion: Thus, in our study patients, infection of multiple MTB strains is a possible cause of TB treatment failure. Explanation for the association between gender and distance of genotypes from the initial to subsequent MTB infection needs further studies