Chlamydia abortus and Chlamydia psittaci are important pathogens of livestock and avian species, respectively. While C. abortus is recognized as descended from C. psittaci species, there is emerging evidence of strains that are intermediary between the two species, suggesting they are recent evolutionary ancestors of C. abortus. Such strains include C. psittaci strain 84/2334 that was isolated from a parrot. Our aim was to classify this strain by sequencing its genome and explore its evolutionary relationship to both C. abortus and C. psittaci.C. abortus species. Furthermore, whole genome de novo sequencing of the strain revealed greater similarity to C. abortus in terms of GC content, while 16S rRNA and whole genome phylogenetic analysis, as well as network and recombination analysis showed that the strain clusters more closely with C. abortus strains. The analysis also suggested a closer evolutionary relationship between this strain and the major C. abortus clade, than to two other intermediary avian C. abortus strains or C. psittaci strains. Molecular analyses of genes (polymorphic membrane protein and transmembrane head protein genes) and loci (plasticity zone), found in key virulence-associated regions that exhibit greatest diversity within and between chlamydial species, reveal greater diversity than present in sequenced C. abortus genomes as well as similar features to both C. abortus and C. psittaci species. The strain also possesses an extrachromosomal plasmid, as found in most C. psittaci species but absent from all sequenced classical C. abortus strains.In this study, methods based on multi-locus sequence typing (MLST) of seven housekeeping genes and on typing of five species discriminant proteins showed that strain 84/2334 clustered with C. psittaci strain 84/2334 clusters very closely with C. abortus strains, and are consistent with the strain being a recent C. abortus ancestral species. This suggests that the strain should be reclassified as C. abortus. Furthermore, the identification of a C. abortus strain bearing an extra-chromosomal plasmid has implications for plasmid-based transformation studies to investigate gene function as well as providing a potential route for the development of a next generation vaccine to protect livestock from C. abortus infection.Overall, the results show that The online version contains supplementary material available at 10.1186/s12864-021-07477-6. Chlamydiaceae comprises a group of obligate intracellular Gram-negative bacteria that are responsible for a broad range of infections in non-human mammals, birds and humans [Chlamydia, and 14 species  [Candidatus species  [The family d humans . Since 1d humans –5. Currehomatis) –8, plus tudinis) –12.C. psittaci that is associated with respiratory, ocular and enteric infections in psittacine birds and poultry [C. psittaci has been classified into nine genotypes based on ompA (major outer membrane protein gene) sequencing [C. gallinacea, C. avium and C. buteonis, have also been found in birds [C. buteonis suggested to have a phylogenetic intermediate position between C. psittaci and C. abortus species [One of the oldest recognised chlamydial species is  poultry , 13. She poultry . Such in poultry . C. psitquencing , of whicquencing . In addiquencing –19. Morein birds , 20, wit species .C. abortus, C. pecorum and C. suis [C. abortus is considered the most closely related to and suggested to be evolved from C. psittaci species [C. abortus is principally responsible for causing enzootic abortion  in sheep and goats [C. abortus also causes sporadic reproductive failure in cattle, horses and pigs and the bacterium presents a dangerous zoonotic risk to pregnant women, in whom it can cause spontaneous abortion, as well as being potentially fatal for the woman [C. psittaci, the genome of C. abortus is considered to be relatively stable with very little diversity and undergoing little or no recombination [Chlamydial infections in non-avian livestock species are principally caused by three species,  C. suis , of whic species . C. abornd goats , 22. Thind goats , generalhe woman –26. In cbination .C. psittaci strains that differ from the classical avian C. psittaci strains, with comparative sequence and MLST analysis suggesting that they are more closely related to C. abortus species [ompA AluI typing, and include isolates Prk/Daruma (isolated from parakeets) [C. psittaci/C. abortus, C. psittaci/C.abortus intermediate and avian C. abortus strains [C. psittaci strains, specifically strain 84/2334, and determine its similarity and genetic relatedness to both C. psittaci and C. abortus species through comparative sequence analysis.It has long been recognised that there are a number of  species , 28. Sucrakeets) , 10,433-rakeets) , VS225 (rakeets) . These irakeets) , have be strains . The purenoA, fumC, gatA, gidA, hemN, hlfX and oppA) [C. psittaci strain 84/2334 as well as other representative strains from each of the currently recognised Chlamydiaceae species are shown in Fig. C. abortus strains, as previously observed using a less robust Neighbour-Joining method [C. abortus strains . Indeed, the strain appears more closely related to the classical C. abortus strains than to the avian C. abortus or C. psittaci strains, which is further supported by in silico genome-to-genome distance comparison [C. abortus and C. psittaci genomes  based on 53 genes encoding the bacterial ribosome protein subunits (rps genes) [C. abortus with 100% support  housekeeping genes (nd oppA) , 32 for g method , as wellC. abortus  and C. psittaci  species and genotypes to determine the percentage sequence identity. Comparison of these sequence similarities for all five discriminant proteins with the threshold scores for distinguishing strains at the species level suggest that strain 84/2334 should be classified as C. abortus  shows that it clusters with those of the two avian C. abortus strains  of strain 84/2334 compared to other representative C. abortus strains is shown in Fig. C. abortus clade and a much larger set common to all the C. psittaci strains. Strain 84/2334 has an intermediate structure, sharing both the regions shared by C. abortus strains and a subset of those common to C. psittaci. Notably, several strains  show greater recombination events unique to the strains. Inclusion of the two avian C. abortus strains in the analysis , polymorphic membrane protein (Pmp) loci and transmembrane-head protein family (TMH) loci of C. psittaci strains GR9, M56 and WS/RT/E30.Comparative analysis of the genome of strain 84/2334 with each of the genomes of the C. psittaci genotypes A, B, D, E, F and WC in terms of gene content, with the one exception, which is that it does not possess the gene encoding the membrane attack complex/perforin domain-containing protein (MACP)  protein family genes or any of the genes involved in L-tryptophan biosynthesis found within or external to the PZ region of some other chlamydial species. Strain 84/2334 is clearly different from the classical C. abortus strains, having an additional six genes, including a large cytotoxin gene (DZK34_02910) and guaB (DZK34_02935) in addition to 4 predicted hypothetical protein genes. However, the large cytotoxin gene is present in the two avian C. abortus strains. Phylogenetic analysis of the predicted protein product of the 84/2334 large cytotoxin gene shows that it clusters with the equivalent predicted proteins of the strains belonging to C. psittaci genotypes A (6BC and 85/55), B (CP3), D (NJ1), E (MN), F (VS225) and WC, while those of the avian C. abortus strains cluster with C. psittaci strains C (GR9), E/B (WS/RT/E30) and M56 , apart from there being fewer of the hypothetical protein genes present between accC and the cytotoxin gene.The PZ of strain 84/2334 most closely resembles that of CP) Fig. . MACP isDZK34_029 and guaBC. abortus and C. psittaci strains shows them to have a high degree of similarity, with the majority of the C. psittaci strains  carrying all 11 of the genes found in C. abortus, differing only in pseudogene content . In contrast, significant differences were noted for C. psittaci strains GR9 and WS/RT/E30, which have a smaller TMH locus with considerably fewer intact genes plus many gene remnants  do not show homology in this region with the typical C. abortus strains or indeed strain 84/2334, rather they are most similar to the smaller TMH loci of C. psittaci strains GR9 and WS/RT/E30.A comparison of the TMH loci of ent Fig. . Strain nts Fig. . The twoC. abortus strains, with the exception of PmpE2 which clustered more closely with the C. psittaci clade along with the equivalent proteins of the two avian C. abortus strains. Considerable expansion in the PmpG family was observed for strain 84/2334, with a total of 13 Pmps identified (five of which are pseudogenes)  tracts. One of these duplications (PmpG12) present in locus 3  domain and a terminal phenylalanine amino acid , 43 Fig. This anC. abortus strains [C. abortus strains . These results were further supported by rMLST, in silico genome-to-genome distance comparisons and 16S rRNA gene phylogenetic analysis, as well as by analysis utilising the recently developed Pillonel typing system [C. abortus species, and closer to classical than avian strains. Interestingly, although not a focus of this study, MLST, rRNA, whole genome and NeighborNet phylogenetic analyses all clearly show that C. buteonis is phylogenetically positioned between both C. psittaci and C. abortus species, as previously suggested [C. psittaci and particularly strain M56.In this study, application of a previously developed MLST typing system , as well strains  by also g system , all shoC. abortus and C. psittaci genotypes [C. abortus and C. psittaci species, the GC content was identical to that of C. abortus rather than C. psittaci species, again suggesting greater similarity with C. abortus. However, strain 84/2334 carries an extrachromosomal plasmid, which is more in keeping with C. psittaci species. Chlamydial plasmids, which are non-conjugative and non-integrative (with the exception of tetracycline resistance in C. suis), have been found in most chlamydial species, including C. psittaci, but to date none have been found in classical C. abortus species [C. abortus strains [C. abortus strains than to those of the C. psittaci genotypes, perhaps reflecting an ancestral relationship with classical C. abortus strains that have lost their plasmid through a process of reductive evolution, where in their specific niche, in a principally mammalian livestock host, the plasmid is not required for tropism and pathogenesis.To characterise strain 84/2334 further we sequenced the whole genome, including plasmid sequence, for a more detailed comparison with previously sequenced representative strains of enotypes , 48–50.  species , 52. How strains , 49, 50.C. abortus clade, in agreement with the typing analyses and also classifies it as an intermediate between the avian and variant/classical C. abortus strains, with branch lengths suggesting a closer evolutionary relationship with classical C. abortus strains. Overall, strain 84/2334 appears much closer to the C. abortus last common ancestor than to the two avian C. abortus strains. Interestingly, recombination has the greatest effect on the phylodynamics of the C. psittaci clade, whereby the placement of strains within the tree structure significantly differs depending on whether phylogenetics is informed or not by recombination. These findings are consistent with previous studies showing that the level of diversity within classical C. abortus strains is low, with only 724 SNPs within the major C. abortus clade and 6718 variable sites within the whole phylogeny (including the variant strain LLG/POS clade) [C. psittaci with 47,710 variable sites [C. psittaci strains.The designation of strain 84/2334 is further supported by whole genome phylogenetic analysis informed by recombination using Gubbins , which uS clade) , while dle sites . OverallC. abortus strain that branched off from the C. abortus last common ancestor at some point between the avian and the classical C. abortus strains. This was supported further through a more detailed analysis of the regions of recombination identified by Gubbins, with strain 84/2334 having an intermediate structure, comprising a couple of regions shared by C. abortus strains plus a subset of those common to C. psittaci, while inclusion of the avian C. abortus strains 15-59d/3 and 15-70d/24 added additional regions of recombination, resulting in a distinctively different pattern and again pointing to 84/2334 being closer in evolution to the non-avian C. abortus strains.Thus, all the analyses, both with and without taking recombination into account, agree with 84/2334 being a misclassified C. abortus, avian C. abortus and C. psittaci strains included in this study, as has been observed for other sequenced chlamydial species [The genome of strain 84/2334 shares characteristic synteny in terms of gene content and order with the classical  species , 53, 54.guaB) and acetyl-CoA carboxylase (accB), has been found to vary markedly in sequence size (approx. 12–82 kb) and gene content (11–44) across chlamydial species [accBC), purine metabolism (guaAB-add) and tryptophan biosynthesis , as well as genes encoding a membrane attack complex/perforin domain-containing protein (MACP), a phospholipase D (PLD) family of proteins, a varying number of cytotoxin/adherence factor proteins and a number of hypothetical proteins of unknown function. Chlamydia abortus has one of the smallest PZ regions amongst chlamydial species, spanning approx. 12 kb, while the PZ of C. psittaci spans approx. 21–30 kb depending on genotype. While these regions differ extensively between C. abortus and C. psittaci, no variation in gene order or content within C. abortus species has been observed [C. psittaci species there are large differences in gene content at these locations in the different genotypes, perhaps reflecting wide-ranging differences in host specificity. The PZ of strain 84/2334, in keeping with classical C. abortus, avian C. abortus and C. psittaci strains does not contain any of the genes involved in L-tryptophan biosynthesis found within or external to the PZ region of some other chlamydial genomes. Overall, while the PZ of 84/2334 is most similar to that of C. psittaci possessing an additional number of similar hypothetical proteins and a cytotoxin gene, it lacks the MACP gene, which is also absent in C. abortus. MACP has been suggested to be involved in assisting PLDs in lipid acquisition and processing [E. coli and C. difficile have a role in glycosylation of Rho and Ras GTP-binding proteins, inhibiting lymphocyte activation, host signalling and blocking the induction of interferon-gamma (IFN-γ) [C. psittaci strains/genotypes, including the avian C. abortus strains, although phylogenetic analysis shows that it clusters with different C. psittaci genotypes than the avian C. abortus strains, perhaps reflecting a different evolutionary path and the ultimate loss of this gene in classical C. abortus strains.The PZ region, which is defined as bounded by genes inosine-5′-monophosphate dehydrogenase  , 57. As  (IFN-γ) , 59, thelpxB) and the polymorphic membrane protein D (pmpD) [n = 8) or single (n = 3) N-terminal transmembrane domains followed by alpha-helical coiled-coil domains of varying lengths, with an amino acid composition rich in leucine, glutamate and serine residues or contain conserved domains of unknown function [C. abortus and C. psittaci strains included in this study) [C. abortus and most C. psittaci genotypes, with some differences in pseudogene content, the main difference is in the absence of the CAB766 gene in 84/2334. This gene encodes the only TMH protein, termed Inc766, to be characterised from this region to date, and which has been shown to form oligomers and to be localised to the extra-inclusion space [C. abortus strains and C. psittaci strains GR9 and WS/RT/E30 is much smaller with considerably fewer intact genes plus many gene remnants, again perhaps reflecting a different evolutionary process for these avian strains compared to strain 84/2334.Another region that has been identified as important in terms of virulence is the TMH locus that typically has 11 genes between the lipid A disaccharide synthase gene (D (pmpD)  that encfunction , 48. Thefunction –62. Theys study) , 44, 48.on space . This poon space , 63, 64.Chlamydia spp. is in the Pmp proteins, which are members of the type V “autotransporter (AT)” secretion system [Chlamydiaceae has been shown to vary considerably from 9 to 21 depending on species, with C. abortus having 18 and C. psittaci 17–21 [C. abortus, suggesting a closer evolutionary relationship. The additional two Pmps in 84/2334 to those found in C. abortus strains result from gene duplication and expansion of the G family from 11 to 13, similar to the number observed in C. psittaci (n = 10–14). However, these gene duplications and the genes they have arisen from possess homopolymeric tracts that are thought to be subject to phase variation by slip-strand mispairing [C. abortus and C. psittaci species/strains, highlights that this is the most diverse and rapidly evolving of all the Pmp families, likely arising and evolving as a result of gene duplications and losses in the various chlamydial ancestries and indicative of the observed recombinogenic nature of this region of the genome [A major source of large-scale variation among n system . Althougn system –68. The ci 17–21 , 53, 69.spairing . These oe genome , 42.C. psittaci strain 84/2334 at the whole genome level using existing typing systems, as well as through whole genome sequencing, comparative genomics and recombination analysis. These analyses show an evolutionary relationship between the strain with both C. abortus and C. psittaci species, in agreement with a previous publication suggesting the strain to be a missing link between C. psittaci and C. abortus and classifying it as an intermediary strain [C. abortus strains than to the avian C. abortus strains or C. psittaci species, branching off from the last common ancestor of C. abortus between the avian and classical strains. These results coupled with the presence of the plasmid sequence which clusters more closely with the avian C. abortus plasmids than the C. psittaci or other chlamydial plasmids, along with taking into account similarities and differences in gene content in key regions and loci associated with virulence, niche specificity and pathogenesis are all consistent with strain 84/2334 being an ancestral C. abortus species. Therefore, overall, the results of this study support the reclassification of this strain as C. abortus species. Future studies should aim to characterise the strain further, investigating its pathogenesis in challenge model systems, as well as with the recent advances in plasmid-based transformation of chlamydial species [In this study we have fully characterised the y strain . However species , 71 begiChlamydia psittaci strain 84/2334, isolated from the lungs of an imported yellow-headed Amazon parrot in Germany [ Germany , was gro Germany . Infecte Germany , and DNAC. psittaci genomes in Table hemB in the oriC region. To identify any reads mapping to a plasmid, the plasmids of C. psittaci strains 6BC and 84/55 , C. abos  and andC. ps1 and G2 , 50). Fo1 and G2  with cru1 and G2 . Genome 1 and G2 .enoA, fumC, gatA, gidA, hemN, hlfX and oppA) of C. psittaci strain 84/2334 and representative strains from Chlamydiaceae species, was performed as previously described [Chlamydiaceae species (except C. trachomatis) in the online database [rps gene database [MLST genotyping of gene fragments of seven housekeeping genes  for each of the five proteins from strain 84/2334 with each of the equivalent proteins from the C. psittaci and C. abortus strains and genotypes in Table A classification scheme, based on five discriminant proteins  for species designation, was applied to strain 84/2334, as previously described . ProteinWhole genome, plasmid, gene  and protein  sequences were aligned using MAFFT v7.450  or ClustC. abortus strains (15-70d/24 and 15-49d/3) present in the alignments.To investigate the effect of recombination on the phylogeny Gubbins version 2.4.1  was usedguaB and accB, and TMH/Inc. locus, typically encoding genes between lpxB and pmpD were manually identified in each of the C. abortus and C. psittaci genomes using ACT [The PZ region, spanning genes between sing ACT . BLAST ssing ACT .C. abortus and C. psittaci genomes using ACT [Gene sequences for the polymorphic membrane proteins (Pmps) were manually checked in each of the sing ACT  to detersing ACT . PredictAdditional file 1: Table S1. Results of rMLST analysis to determine species classification using the rps gene database at https://pubmlst.org/species-id.Additional file 2: Fig. S1. Minimum spanning tree illustrating cluster analysis of MLST sequence type (ST) profiles. Cluster analysis is based on nucleotide differences in seven MLST housekeeping gene fragments . STs for strain C. psittaci strain 84/2334 and representative strains from Chlamydiaceae species (excluding C. trachomatis) are indicated .Additional file 3: Fig. S2. Phylogenetic tree of a 16S rRNA gene alignment of strain 84/2334 and other Chlamydiaceae species. The consensus tree for the 1470 bp alignment was estimated in TOPALi by Neighbour Joining using a F84 + G substitution and rate heterogeneity model and 100 non-parametric bootstrap replicates. The tree is midpoint rooted and bootstrap support is indicated by the number at the node. The scale bar indicates the expected substitutions per site. Genotypes are given in square brackets. The tree was prepared in Dendroscope. Strain 84/2334 is in bold and red font.Additional file 4: Table S2. Results of digital DNA-DNA hybridization to determine species using the Genome-to-Genome Distance Calculator 2.1 at http://ggdc.dsmz.de/ggdc.php.Additional file 5: Fig. S3. Whole genome phylogenetic analysis informed by recombination with added outgroup. Phylogenetic tree of a whole genome sequence MAFFT alignment of the C. abortus (Cab) and C. psittaci (Cps) strains shown in Table C. pecorum W73 was additionally provided as outgroup. FastTree was used as tree builder, and a maximum of 100 iterations was specified in order to guarantee convergence. Tree was midpoint rooted and prepared using Dendroscope. Strain 84/2334 is in bold and red font. Classical and avian C. abortus strains are in blue and green fonts, respectively.Additional file 6: Fig. S4. Whole genome phylogenetic analysis. Phylogenetic tree of a whole genome sequence MAFFT alignment of the C. abortus (Cab) and C. psittaci (Cps) strains shown in Table C. buteonis strain RSHA. The consensus tree was estimated in IQ-Tree by Maximum Likelihood using a TVM + F + R2 substitution and rate heterogeneity model, according to BIC model selection, and 100 non-parametric bootstrap replicates. The tree is midpoint rooted and bootstrap support is indicated by the number at the node. The scale bar indicates the expected substitutions per site. Genotypes are given in square brackets. The tree was prepared in Dendroscope. Strain 84/2334 is in bold and red font. Classical and avian C. abortus strains are in blue and green fonts, respectively.Additional file 7: Fig. S5. Whole genome NeighborNet network analysis. Phylogenetic network of a whole genome sequence alignment of the C. abortus (Cab) and C. psittaci (Cps) strains shown in Table C. psittaci and avian C. abortus strains are indicated in brackets. The figure was generated using SplitsTree4. Strain 84/2334 is in bold and red font.Additional file 8: Fig. S6. Summary of Gubbins recombination analysis including avian C. abortus strains 15-59d/3 and 15-70d/24. The red blocks represent recombination events occurring on an internal branch of the phylogenetic tree, which are shared by several strains by common descent. The blue blocks indicate recombination events occurring on terminal branches of the phylogenetic tree, which are unique to a specific strain. The parameters used for the run are those described in Fig. Additional file 9: Fig. S7. Comparative genome analysis of C. psittaci 84/2334. Whole genome comparisons of C. psittaci strain 84/2334 and (A) C. abortus strains S26/3, AB7 and LLG and (B) representative C. psittaci strains VS225, 84/55, GR9 and M56 depicting amino acid matches computed using Megablast blastn. Homology matches are indicated by the red vertical bars, while inverted matches (indicating areas of recombination) are coloured blue. Horizontal grey bars represent the forward and reverse strands of DNA with CDSs marked as arrows. The main regions of difference occur in two of the Pmp loci (circled areas 1 and 3), the PZ region (circled area 2) and TMH loci (circled area 4). Please note that the gaps shown for C. abortus strain LLG compared to 84/2334 in Pmp loci (circled areas 1 and 3) are due to the sequences not being complete in these regions rather than homology differences. The figure was generated using the Artemis Comparison Tool (ACT).Additional file 10: Fig. S8. Phylogenetic analysis of chlamydial cytotoxin predicted protein sequences. The consensus tree was estimated in IQ-Tree by Maximum Likelihood using a JTTDCMut + F + I + G4 substitution and rate heterogeneity model, according to BIC model selection, and 100 non-parametric bootstrap replicates. The tree is midpoint rooted and bootstrap support is indicated by the number at the node. The scale bar indicates the expected substitutions per site. The tree was prepared in Dendroscope. Strain 84/2334 is in bold and red font.Additional file 11: Fig. S9. Polymorphic membrane protein family phylogenies. Consensus trees for singleton PmpA, PmpB, PmpD and PmpH family members (A), for the PmpE family members (B) and PmpG family members (C) for strain 84/2334 and the C. abortus and C. psittaci strains/genotypes shown in Table C. abortus strains are in blue and green fonts, respectively.


Abnormal DNA methylation, an epigenetic modification, has increasingly been linked to the pathogenesis of many human cancers. However, there has been little focus on the DNA methylation patterns of genes encoding long noncoding RNAs (lncRNAs) in gastric cancer (GC). This study comprehensively determined DNA methylation and lncRNA expression profiles in GC through genome-wide analysis. Differentially methylated loci and lncRNAs were identified by integrating multi-omics data. In total, 548 differentially methylated CpG sites in lncRNA promoters and 2,399 differentially expressed lncRNAs were screened that were capable of distinguishing GC from normal tissues. Among them, 22 differentially methylation sites in 17 lncRNAs were inversely related to expression levels. Further analysis of DNA methylation status and gene expression level in GC revealed that three CpG sites  and two lncRNAs (RP11-366F6.2 and RP5-881L22.5) were significantly associated with GC patient overall survival. Molecular function analysis showed that these abnormally methylated lncRNAs were mainly involved in transcriptional activator activity. Our study identified several lncRNAs regulated by aberrant DNA methylation that have clinical utility as novel prognostic biomarkers in GC. These findings help improve the understanding of methylated patterns of lncRNAs and further our knowledge of the role of epigenetics in cancer development. Gastric carcinoma (GC) is the fourth most prevalent malignancy and third leading cause of cancer death worldwide . HistoloLong noncoding RNAs (lncRNAs) are loosely defined as RNAs more than 200 bases in length with no apparent coding capacity . LncRNAsHere, we employed multigenomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets to systematically characterize global DNA methylation levels, lncRNA expression profiles, and clinical features in GC. Our results decode the landscape of DNA methylation-mediated regulation for lncRNAs and provide promising biomarkers in the diagnosis and treatment of GC.https://xenabrowser.net/). A Human Methylation27 BeadChip array of GC (GSE30601) was obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). Level-3 RNA-sequencing data (HTSeq-Counts and HTSeq-FPKM-UQ) and the clinicopathological and survival data of GC patients were also downloaded from the Xena website.The DNA methylation array data  were downloaded from the UCSC Xena browser (http://www.bioconductor.org/packages/release/bioc/html/minfi.html) (http://zwdzwd.io/InfiniumAnnotation). The coordinates of the individual lncRNA were extracted from GENCODE v22 (https://www.gencodegenes.org/human/release_22.html). After the preprocessing the coordinates of CpG sites and lncRNAs, we further integrated both information based on the genomic location, considering differentially methylated loci within promoter regions . Manhattan plot was constructed to depict the distribution of CpG sites according to FDR via qqman package   and differentially methylated regions (DMRs) between GC samples and adjacent tissues were identified using the minfi package  . Bump hufi.html) . The genex.html) .https://bioconductor.org/packages/release/bioc/html/edgeR.html)  . LncRNA The correlation analysis between DMCs and DElncs was calculated and those with |coefficient of correlation| > 0.3 and P-value < 0.05 were considered significant. The visualization of the potential regulation of CpG sites to genes was constructed in Cytoscape 3.7.1 .https://bioconductor.org/packages/release/bioc/html/clusterProfiler.html) was used to perform Gene Ontology (GO) function and Gene Set Enrichment Analysis (GSEA) for DElncs with the DMCs (https://bioconductor.org/packages/release/data/annotation/html/org. Hs.eg.db.html). The value of log2 (FC) calculated by edgeR package was used as ranking metric for GSEA. We used the canonical pathways sub-collection of the C2 collection in the Molecular Signatures Database as the gene sets in the analysis. The leading-edge subset of genes in an enriched gene set are defined as those that appear in the ranked list before the point at which the running sum reaches its maximum deviation from zero.ClusterProfiler tool  and two lncRNAs (RP11-366F6.2 and RP5-881L22.5) with P < 0.05. Forest plot demonstrated that the methylation of the three probes and two lncRNAs were associated with the overall survival time of GC patients Table 1.To better understand the biological function of the 17 DElncs, we constructed a co-expression network of deregulated protein-coding genes and lncRNAs. Using the Spearman's correlation coefficient above 0.8, a total of 32 deregulated mRNAs co-expressed with five lncRNAs  were acquired for GO enrichment analysis. Only nine protein-coding genes associated with HOTAIR, HOXC-AC3, and ZNF667-AS1 were assigned GO molecular function, involving oxidoreductase activity, nucleotide diphosphatase activity, and transcriptional activator activity  in GC that were significantly associated with overall survival. RP11-366F6.2, also called MAGEA4-AS1, is located in chrX and was reported to have significantly high expression in several tumor tissues, such as breast cancer and laryngeal squamous cell carcinoma . AlthougTo investigate the effect of epigenetically deregulated lncRNA in biological processes and pathways, an integrated analysis of DElncs and predicted mRNAs expression was performed. GO analysis revealed that these lncRNAs were involved in dysregulated transcriptional programs that invariably lead to cancer. We also found that predicted mRNAs HOXC10 and MSRB3 in GO analysis were significantly associated with overall survival in GC patients .Several limitations in the present study should be pointed out. First, integrated analysis of genome-wide DNA methylation and lncRNA expression was based on the 27K Illumina array platform, which only contained 27,578 individual registered probes, and thus some possibly important methylation differences may be lacking from the current results. Second, the results of the present study are preliminary and primarily derived from bioinformatics analysis, and lack functional validation of the epigenetically deregulated lncRNAs. Third, due to limited availability of clinical data, it was not possible to obtain deeper insights into characterizing phenotype-genotype relationships.In conclusion, the present results provide evidence for the changes of widespread DNA methylation of lncRNA-encoding genes in GC patients. The candidate factors identified in this study might function as potential molecular phenotypic biomarkers, especially RP11-366F6.2 and RP5-881L22.5, which were associated with prognosis. Our results help elucidate a more detailed explanation of epigenetic mechanisms for GC and deepen our understanding of the aberrantly methylated patterns in lncRNA-encoding genes.The following information was supplied regarding data availability:.The level 3 TCGA data for DNA methylation arrays and lncRNA expression are available in Xena website.https://gdc.xenahubs.net/download/TCGA-STAD.methylation27.tsv.gzHumanMethylation27: https://gdc.xenahubs.net/download/TCGA-STAD.methylation450.tsv.gzHumanMethylation450: https://gdc.xenahubs.net/download/TCGA-STAD.htseq_counts.tsv.gzHTSeq-Counts: https://gdc.xenahubs.net/download/TCGA-STAD.htseq_fpkm-uq.tsv.gzHTSeq-FPKM-UQ: https://gdc.xenahubs.net/download/TCGA-STAD.GDC_phenotype.tsv.gzPhenotype: https://gdc.xenahubs.net/download/TCGA-STAD.survival.tsv.gzSurvival data: The microarray data that support this study are available through the NCBI database under accession GSE30601.The data used to support the findings of this study are included within the article.PS and WG designed the study. PS and LW collected, analysed and interpreted the data. PS and LW wrote the draft. PS and WG edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Bacteroides [Bacteroides fragilis has resulted in an ever-expanding pangenome, revealing substantial genetic diversity within the species  type strain NCTC 9343 directs a tolerogenic immune response, suppressing intestinal inflammation in mice [B. fragilis (ETBF) strains drive inflammation of the colon and are associated with colorectal cancer [B. fragilis toxin (BFT), a metalloprotease that causes barrier disruption and intestinal inflammation [B. fragilis pathogenicity island (BfPAI), that is flanked by genes encoding mobilization proteins  [B. fragilis strains likely reflect a continuum instead of a dichotomy. in mice ,25. Howel cancer –29. A diammation ,30. BFT nsposon) . These mnsposon) . Indepenbft isotypes  [bft isotype may contribute to the seemingly variable pathogenicity among ETBF strains [bft-1 and bft-2 exhibit slightly higher cytotoxicity compared to strains containing bft-3 [bft variants and chronic inflammatory diseases.Although ETBF is associated with disease, up to 30% of individuals who harbor ETBF do so asymptomatically . This di, bft-3) . The pre strains . For exa strains ,36. In Hng bft-3 . BecausempII encodes for another metalloprotease with potential pathogenic properties [bft, could contribute to disparities in pathogenicity [Adding even more complexity, BFT may not be the only virulence factor in ETBF. Within the BfPAI, operties . In a geoperties . Variatigenicity . Comparegenicity . The conB. fragilis also promotes immune tolerance in the gut. The type strain B. fragilis NCTC 9343 expresses PSA, which drives regulatory T cells to produce interleukin-10, an anti-inflammatory cytokine responsible for maintaining immune tolerance [B. fragilis strains promote this PSA-dependent immune response, but varied host responses may arise from variation in the expression and structure of PSA among strains. In a study of 50 diverse B. fragilis strains, the regions flanking the PSA locus were found to be conserved [B. fragilis PSA. The commonly used lab strain B. fragilis 638R exhibited a distinct PCR product within the PSA locus [B. fragilis in the human population. Of note, recent genetic comparisons reveal that the PSA locus of NCTC 9343 is not conserved in B. fragilis HMW615 or B. fragilis 638R [Despite its associations with disease, olerance ,25. It ronserved . HoweverSA locus , raisinglis 638R .B. fragilis PSA locus suggests variability in PSA structure [B. fragilis is associated with inflammation, the PSA of B. fragilis NCTC 9343 was a more potent inducer of peritoneal abscess formation in a rat model compared to the PSA of B. fragilis 638R [B. fragilis is capable of suppressing inflammation. Therefore, PSA variation among strains may influence the induction of a tolerogenic response required for maintaining homeostasis [B. fragilis strains warrants further study, given that the relationship between the host immune system and NTBF is strain-dependent.The extensive variation in the tructure . Consisttructure ,39. Outslis 638R . Within eostasis ,12,37. TB. fragilis lab strains, including NCTC 9343 and 638R [B. fragilis in the context of immune tolerance in the gut [B. fragilis NCTC9343 did not significantly affect the production of pro-inflammatory cytokine tumor necrosis factor alpha (TNF-α), whereas a B. fragilis strain isolated from a healthy donor, B. fragilis HCK-B3, down-regulated TNF-α [B. fragilis strains can exhibit varied sensitivity to immune mediators in the gut. Fecal isolates are more susceptible to the antimicrobial peptide, human β-defensin-3, compared to blood and extraintestinal isolates [B. fragilis strains may be more likely to translocate out of intestinal tissue and cause disease. The intestinal environment, in either healthy or pathologic conditions, shapes the adaptive strategies of bacterial strains. Over the course of our life span, the changing gut environment  presents opportunities for new strains to evolve, driving genomic and functional diversity.Common and 638R , were or the gut ,25. Clin the gut . For exaed TNF-α . Furtherisolates . By evadB. fragilis serves as an example to illustrate the range of phenotypic heterogeneity within a commensal species. By studying bacterial strains across different populations, we can gain insight into genes and functions that are under selection in the human microbiota. For instance, how might chronic inflammatory conditions drive strain selection and divergence? We predict that prolonged inflammation in a sick individual may give rise to B. fragilis strains that are distinct from those found in a healthy individual, but further work is needed to validate this notion. On the other hand, how might strain diversity influence disease outcomes? Deeper examination of bacterial strains associated with disease may uncover pathological phenotypes driven by select strains. For example, genomic analysis revealed that specific B. fragilis strains were associated with type 2 diabetes [B. fragilis. Strains of gut commensal Eggerthella lenta show differences in the ability to inactivate the cardiac drug digoxin, which can affect clinical outcomes [Prevotella copri strains from Western populations and non-Western populations show significant genetic differences [Emerging technologies have illuminated the rich diversity of bacterial strains in the human microbiome. diabetes ; howeveroutcomes . Moreoveferences . The unp


Brassica napus (canola/oilseed rape/rapeseed) is an economically important crop, mostly found in temperate and sub-tropical regions, that is cultivated widely for its edible oil. Major diseases of Brassica crops such as Blackleg, Clubroot, Sclerotinia Stem Rot, Downy Mildew, Alternaria Leaf Spot and White Rust have caused significant yield and economic losses in rapeseed-producing countries worldwide, exacerbated by global climate change, and, if not remedied effectively, will threaten global food security. To gain further insights into the host–pathogen interactions in relation to Brassica diseases, it is critical that we review current knowledge in this area and discuss how omics technologies can offer promising results and help to push boundaries in our understanding of the resistance mechanisms. Omics technologies, such as genomics, proteomics, transcriptomics and metabolomics approaches, allow us to understand the host and pathogen, as well as the interaction between the two species at a deeper level. With these integrated data in multi-omics and systems biology, we are able to breed high-quality disease-resistant Brassica crops in a more holistic, targeted and accurate way. Plants interact very closely with microorganisms, such as fungi and bacteria, in the natural environment through a symbiotic relationship with endophytes, often having beneficial effects on the plant . By contR) gene in the host and the effector  gene in the pathogen [R genes, during defence signalling.Plants, in response, protect themselves from pathogen attack typically through two divisions of immunity. The first is the innate immune response, also known as PAMP (pathogen-associated molecular pattern)-triggered immunity (PTI). This provides defence against a broad range of pathogens involving cell surface plant pattern recognition receptors (PRRs) recognising extracellular PAMPs. The second is adaptive immunity, also referred to as effector-triggered immunity (ETI). This provides complete resistance to the host and is mediated by a specific interaction between the resistance  belonging to the family Brassicaceae. The Brassicaceae constitute 325 genera and 3740 species [Brassica having 73 accepted species [Brassica species are B. rapa (AA genome), B. nigra (BB genome), B. oleracea (CC genome), B. napus (AACC genome), B. juncea (AABB genome) and B. carinata (BBCC genome). These six species are cultivated as vegetables, oilseeds and condiments, and display a wide variety of morphotypes, including as leafy vegetables such as Chinese cabbage and pak choi in B. rapa, the enlarged inflorescences of cauliflower and broccoli in B. oleracea, and the condiment seeds of mustard plants in B. nigra and B. juncea [B. napus is an oilseed crop that is traded globally and a major cash crop [B. napus is widely grown in Europe, Canada, China and Australia [B. napus crop yield for high-quality and sustainable production to meet the growing demand of food consumption. This faces two challenges—first, the predicted increase in the human population to 9 billion by 2050, and second, the impact of unpredicted weather patterns worldwide due to global climate change [ species ,12, with species ,14. The . juncea ,16. B. nustralia  and rankustralia . There iB. napus plays host to several fungal pathogens that cause major diseases leading to substantial loss in global production. These diseases include Blackleg , Clubroot (obligate biotrophic protist/chytrid Plasmodiophora brassicae), Sclerotinia Stem Rot  [Hyaloperonospora brassicae), Alternaria Leaf Spot , and White Rust (obligate biotrophic oomycete Albugo candida) [B. napus industry, with the potential to wipe out the entire crop where not effectively controlled [Brassica is through breeding disease-resistant varieties [B. napus pathosystems, integrating technologies from both the host and pathogen, are pertinent in breeding Brassica varieties that are better able to resist pathogen attack (otiorum) , Downy Mcandida) ,23. Thesntrolled ,27,28,29arieties . In thisn attack .B. napus and other Brassica crops. We first discuss the application of omics technologies in the host, in relation to the identification of candidate QTL/R genes. We then discuss progress in pathogen research, focusing on the application of omics tools in the discovery of pathogenicity genes. Lastly, we review future perspectives and prospects for the utilisation of omics technologies in Brassica–pathogen research for breeding high-quality, more-resistant crop varieties.Here, we review the current status of the application of omics technologies to understand the molecular aspects of host–pathogen interactions in Brassica crop genomes  have now been sequenced, with some species having more than one genome from different individuals [Brassica genomics has been “revolutionised” by the development of long-read sequencing technologies such as PacBio Single Molecule, Real-Time (PacBio) sequencing [Brassica–pathogen interactions have been provided via high-quality genome assemblies of Brassica species using PacBio sequencing, for example, B. rapa cultivar “Chiifu-401-42” [B. oleracea cultivar “C-8” [B. napus German winter cultivar “Express 617” [B. napus “Darmor-bzh” [B. nigra assembly, both achieved via ONT technology (Brassica assemblies resolve the “difficult” genomic regions commonly found in polyploid crops [With the introduction of next-generation sequencing (NGS) technology, five out of six ividuals ,32,33. Tquencing  and Oxfoquencing , along wquencing  and Chroquencing ,38. Valu-401-42” , B. olermor-bzh” , along wchnology . These hid crops ,44,45.Brassica genome assemblies are currently available, such reference genomes and other Brassica genomes that were previously sequenced represent only a fraction of the Brassica morphotypes. For example, the reference B. rapa “Chiifu” is a heading type [B. oleracea “C-8” is an inflorescence type [Brassica species, such as root or stem tubers in B. rapa (turnip), B. oleracea (kohlrabi) and B. napus (swede) [Brassica species, but also that a wealth of novel alleles for disease resistance are potentially overlooked if we rely on a single reference genome. These issues have driven the development of pangenomes in plants.Although high-quality ing type , while ting type , the caunce type , and “TOnce type . That ge (swede) , means tB. napus, which was built with eight B. napus lines encompassing three ecotypes using a de novo approach, showed the PAV regions were enriched with genes associated with a defence-related response [B. oleracea and B. napus pangenomes, it was found that a large proportion of the disease resistance genes were dispensable, meaning that these genes are not present in all lines [R genes in Brassica are highly variable, resulting from the strong selection pressure of arms-race evolution during host–pathogen interaction, superimposed by the frequent homoeologous exchanges between sub-genomes [Brassica lineage [R genes may have been missed from a single reference genome, thus hindering the speed of R gene cloning in Brassica crops.Pangenomics has been developed to overcome the limitations of relying on a single reference genome, and allows more comprehensive genomic variations to be identified from the gene pools represented by many lines within a species ,49,50. Tresponse . Furtherll lines ,52 , in Brassica species. Examples of RGAs include nucleotide-binding site leucine-rich repeats (NLRs), mainly comprising the TIR-NBS-LRR (TNL) and CC-NBS-LRR (CNL) types, receptor-like protein kinases (RLKs), receptor-like proteins (RLPs) and wall-associated kinases [B. napus pangenome [B. oleracea pangenome [R gene variability and resistance outcomes in Brassica crops for the major diseases? It was also found in the B. oleracea pangenome study that the wild relative B. macrocarpa harbours the most RGA candidates, suggesting that a large pool of genetic resources for R genes can be found in wild Brassicas [Brassica crops, not only can we identify many more novel candidate disease resistance genes from the wild genotypes, but we can also develop molecular markers to screen for resistant varieties in the field, therefore not only improving the speed and accuracy of crop breeding but also broadening the Brassica gene pool by using novel alleles from wild germplasm.Pangenomics has identified a large  kinases ,54. Usinangenome  while 59angenome . These prassicas ,52. Recerassicas . With a Brassica crops have been generated, using bi-parental crossing, selfing and backcrosses, with molecular markers such as Restriction Fragment Length Polymorphisms (RFLPs), Amplified Fragment Length Polymorphisms (AFLPs) and Randomly Amplified Polymorphic DNA (RAPDs) reviewed by Delourme, et al. [Brassica crops [Brassica crops through the development of genome-wide DNA-based molecular markers. This has brought great improvement in the resolution of genetic maps [In the past two decades, many genetic linkage maps of , et al. . These mca crops . The gentic maps .Brassica species through systems such as whole-genome resequencing (WGRS), genotyping-by-sequencing (GBS), and the Brassica 60K Illumina InfiniumTM 60K SNP array [Among the DNA-based molecular markers, single nucleotide polymorphism (SNP) markers are most widely used for determining genotypic variation in a given species because they are uniformly distributed and highly abundant in the genome and are amenable in multiple genotyping platforms ,62. WithNP array .Brassica reference genome assemblies [® using oligonucleotides instead of adaptors has since been developed [Brassica germplasm [Brassica lines [WGRS is an omics strategy for obtaining high-quality, high-density SNP markers at a whole-genome level by mapping sequence reads to the semblies . In GBS,semblies . In thissemblies ,66. An eeveloped . The Braermplasm ,69,70. Aca lines , permittBrassica crops  in ca crops . Highlig quality . In addiectively .Brassica genomics resources in public databases supports the analysis and interpretation of many complex mechanisms related to Brassica–pathogen interaction. Examples include the in silico identification of the Blackleg resistance gene, LepR4, in the C genome of Korean cabbage (B. oleracea var. capitata) [B. napus, together highlighting the genomic distribution and structural variation of these genes in B. napus [B. napus, where comparative genomic analysis highlighted the NBS gene’s distribution from its progenitors B. rapa and B. oleracea in relation to the three main Brassica diseases—Blackleg, Clubroot and Sclerotinia [Brassica host and the fungal pathogens [Brassica crop improvement research investigations.The large volume of apitata)  and the B. napus . Other eerotinia . Coupledathogens . This isR genes in B. napus that are associated with Blackleg, Sclerotinia and Clubroot resistance [B. napus and its progenitors, B. rapa and B. oleracea, revealed many more NBS  genes in the C sub-genome of B. napus. A number of these genes underly the QTL regions for resistance against Blackleg, Sclerotinia and Clubroot, supporting the concept that the diversification of the R genes likely happened after interspecific hybridisation between B. rapa and B. oleracea [In addition, database searches for protein motifs associated with disease resistance genes have enabled researchers to identify classes of sistance . Stotz, sistance  suggest oleracea .Brassica–pathogen interactions. This technique involves bulks/pools of DNA samples with representations of individuals with segregating phenotypes, where the pools are genotyped using NGS, either RNA sequencing (BSR-Seq) or whole-genome resequencing, followed by the detection of QTLs through SNP calling between the bulks (QTL-Seq) [NGS-based BSA is one of the more recent applications of omics in studying QTL-Seq) ,94. The QTL-Seq) , but it QTL-Seq) .R gene for resistance against Blackleg, Rlm1, was fine mapped in the B. napus cultivar “Quinta”, and a candidate gene was identified, BnA07G27460D, that encodes a serine/threonine protein kinase. This gene is homologous to the protein kinase STN7 in B. rapa, B. oleracea and A. thaliana, which is involved in systemic plant immune responses by regulating reactive oxygen species (ROS)-induced cell signalling at the thylakoid membrane [Brassica speciesl; for example, in B. oleracea, the first Clubroot major R gene (Rcr7) in the B. oleracea cultivar “Tekila” was identified; Bo7g108760 was the candidate TNL gene [B. rapa var. pekinensis, the candidate gene Rcr2, which encodes a TIR-NBS-LRR, responsible for Clubroot resistance, has been identified on chromosome A03 [B. nigra, a novel Clubroot R gene, Rcr6, was detected , which is homologous to chromosome A08 of B. rapa and which provides a good source for gene introgression into B. napus [B. campestris var. chinensis [R gene, also involved in Clubroot resistance, CRd, was identified on chromosome A03 of B. rapa [Using BSR-Seq, an membrane . BSR-SeqTNL gene . In Chinsome A03 . In B. nB. napus . Using Qhinensis . Lastly, B. rapa .A. thaliana to study the R gene sequence variants of the White Rust Resistance (WRR) gene against Albugo candida [A. thaliana to study the evolution and variability of NLR genes in the model plant Arabidopsis, resulting in the construction of a species-wide pan-NLR-ome [A. thaliana [R genes can be obtained from the diverse gene pool of NLRs within members of the Brassicaceae family, including Brassica crops. The discovery of a repertoire of NLRs is particularly important when pathogen-specific recognition can not only happen in the host species but also in the non-host species. For example, the non-host A. thaliana displayed ETI-mediated defence against A. candida isolates derived from B. juncea, B. rapa and B. oleracea [R genes play a conserved role across members within the same family. This implies that screening for novel R genes for Brassica crop improvement should also be applied across non-host species. Pan-NLR-ome type studies contribute significantly towards the discovery of R gene diversity in crops.RenSeq is a targeted resequencing method for identifying NLRs . RenSeq  candida . This co-NLR-ome . Similarthaliana . This imoleracea , implyinR genes in crop plants, although R gene products may not necessarily interact with effectors directly. In this method, the target effector, as forecast from prediction tools, is transformed using Agrobacterium and infiltrated onto the host plants. The host genotypes that give a positive response to the target effector are then subjected to resistance gene mapping using molecular markers [R genes in the wild potato species S. pinnatisectum against the oomycete Phytophthora infestans [Brassica pathosystems for the identification of R genes.Effectoromics, or effector-based screening, is an omics approach to detecting  markers . Effecto markers . This menfestans ,108 and Plant–pathogen interactions are complex, involving a breadth of interconnected molecular mechanisms . CriticaGene expression analysis has already significantly evolved since early techniques were described and developed . Recent Brassica crops. AT is an RNA-based approach that integrates transcriptome data in GWAS to identify molecular markers associated with a particular trait of interest at marker loci where the levels of gene sequence and gene expression are variable [Furthermore, integrative approaches such as associative transcriptomics (AT)  and bulkvariable . AT is pvariable .B. napus resistance against Blackleg, three of the known R genes have been cloned and were found to encode Leucine-Rich Repeats-Receptor Like Proteins  and a wall-associated kinase-like (WAKL) protein (Rlm9) [LepR3 and Rlm2 evoked a basal defence response in both compatible and incompatible interactions upon inoculation with L. maculans isolates. This suggests that LepR3 and Rlm2 may also monitor other molecular patterns produced by L. maculans to mount a resistance response in the host plant.In n (Rlm9) ,117. Then (Rlm9)  found thRlm9 WAKL protein is a type of receptor-like kinase (RLK) localized in the cell wall, which functions to sense environmental and cellular signals [Rlm9 is only the second WAKL R-gene identified to date; hence, the mechanisms underlying its resistance are yet to be studied in detail. Initially, Larkan, et al. [Rlm9 did not seem to have a direct interaction with its counterpart Avr gene (AvrLm5-9), and it is likely that a mediator molecule, such as damage-associated molecular patterns (DAMPs), is needed to effect resistance. This is supported by the findings of Brutus, et al. [Rlm9 orchestrates race-specific resistance responses against the Blackleg pathogen. Furthermore, as Rlm9 forms part of the tightly linked R-gene cluster (Rlm3/4/7/9) on chromosome A07 of B. napus, the cloning of this gene may enable an understanding of the molecular mechanisms of the other genes on this cluster.The  signals . Rlm9 is, et al.  found Rl, et al. , which sRlm2, Rlm3, LepR1 and LepR2 in cultivar “Topas” and LepR1 and LepR2 in “Westar” allowed the comparison of the effect of genetic background and R gene content in host defence expression through genome-wide transcriptome profiling by Haddadi, et al. [LepR1 and Rlm2 compared with LepR2 and Rlm3 lines during the first three days of infection. Furthermore, a general trend of delayed defence responses in “Westar” compared with “Topas” ILs was observed, regardless of their R gene content. This suggests that the genetic background has important effects on resistance. Additionally, there was enhanced expression of the RLK Brassica napus (Bn) SOBIR1 (Suppressor of BIR1-1) and salicylic acid-related defence in both LepR1 and Rlm2 lines, consistent with previous investigations [B. napus–L. maculans interaction [Avr genes in L. maculans likely play a role in manipulating host resistance in the apoplast environment. The AvrLm1 protein reportedly interacts with the mitogen-activated protein kinase (MAPK) 9 in B. napus (BnMPK9) [Bn-SOBIR with Rlm2, and it was assumed that the Rlm2 and Bn-SOBIR interaction results in downstream signalling to effect race-specific resistance against the AvrLm2 L. maculans pathotype. Given this information, it is likely that LepR1 conveys resistance through the same mechanism. Conversely, the expression of Bn-SOBIR was low in Rlm3 introgression lines, which means that Rlm3 not only functions independently of the SOBIR1 interaction but represents another resistance mechanism different from that of other cloned genes. The cloning and transcriptomic analysis of this gene will shed light on the molecular mechanisms governing the operation of this resistance [The introgression of the major genes , et al. . All theigations ,118,122.eraction . All the(BnMPK9) . Further(BnMPK9) ,126. Lar(BnMPK9)  previoussistance .B. napus–Clubroot pathosystem, several R genes acting against P. brassicae have been mapped, but only two have been cloned: CRa [Crr1a [B. napus containing two Clubroot resistance genes, PbBa8.1 and CRb, with the candidate genes involved in the hormone signalling pathway identified through comparative RNA-seq [CRb-containing B. rapa lines, at the early stages of P. brassicae infection, confirmed the involvement of pathways typical for ETI-mediated resistance and biotrophic infection [Rcr1-mediated resistance in B. rapa, thus highlighting a complex molecular mechanism for P. brassicae resistance in Brassica crops. The cloning of the Rcr1 gene will help to elucidate these hormones’ induction dynamics. However, whilst Crr1a and CRa have been cloned, the transcriptional control of their resistance has not been widely researched. Genome-wide transcriptome studies should help to elucidate the resistance mechanisms involved in these two key clubroot R genes. To study the genetic effects of the multiple R genes in pyramided lines and confirm the role of these introgressed genes in host resistance responses, comparative RNA sequencing could be performed. For example, when two Clubroot-resistant genes, PbBa8.1 and CRb, were introgressed into a B. napus-pyramided line, through comparative RNA sequencing, it was found not only that the pyramided lines displayed a strong multi-gene resistance network during pathogen infection, but also that SA- and ROS-mediated resistance responses played a dominant role in the pyramided lines [B. napus–P. brassicae pathosystem.In the ned: CRa  and Crr1a [Crr1a , which e RNA-seq . The tranfection . These infection ,132,133.nfection  highlighed lines , supported lines ’s study,B. napus, Qasim, et al. [R gene that is associated with a qualitative response, was highly transcribed [R-gene host-mediated resistance mechanisms shown in the study mirrors the complexity of quantitative resistance. Some of the described mechanisms are atypical of PTI- and ETI-mediated host defences, supporting an ongoing discussion challenging the applicability of the conventional two-tier model of plant immunity in explaining quantitative resistance variation. This enigma may be due to the differences in the hosts and the pathogens, as well as the approaches employed for studying genome-wide gene expression. Nevertheless, the increasing availability of transcriptome data generated through various high-throughput platforms results in a better comprehension of the mechanisms underpinning quantitative resistance. Global transcription sequencing also revealed that JA and ET signalling were associated with a resistance response against S. sclerotiorum in B. napus [B. napus NPR1-like gene, BnaNPR1, which plays a role in SA and JA signalling, indicating that S. sclerotiorum suppresses the expression of BnaNPR1 during systemic acquired resistance (SAR) for successful invasion into the host cell [B. napus using two NBS-LRR genes, pro−1BvHs1 and BvcZR3, obtained from nematode (Heterodera schachtii)-resistant sugar beet [In a study of Sclerotinia resistance in , et al.  detectednscribed . As ScleB. napus ,138; a fost cell . It is agar beet . The genB. napus–S. sclerotiorum pathosystem showed that indolic glucosinolate biosynthesis plays an important role [B. napus, one of which, BnUGT74B1, encoding cytochrome P450, enhanced resistance to S. sclerotiorum [B. oleracea–S. sclerotiorum interaction revealed a total of 45 B. oleracea genes involved in Ca2+ signalling were upregulated, which is important in ROS generation [B. oleracea showed ROS generation and increased Ca2+ signalling contributing towards resistance outcomes in B. oleracea [Comparative transcriptomic analysis of the ant role , similarrotiorum . Transcrneration , and thioleracea .H. brassicae)-infected Chinese cabbage lines demonstrated the involvement of protein processing in endoplasmic reticulum and circadian rhythm pathways in resistance mechanisms [H. brassicae infection, which is consistent with Xiao, et al. [H. brassicae in Brassica crops may be driven by efficient energy metabolism during pathogen invasion.A transcriptome study of Downy Mildew , which are involved in Ca2+ signalling, were highly expressed in the resistant genotype at 4 h after infection [B. oleracea in response to the black rot pathogen (X. campestris), highlighted the role of Ca2+ signalling proteins as secondary messengers for several downstream signalling processes, including the activation of several transcription factors responsible for the initiation of SA-mediated host defence. The deep RNA-seq of Liu, et al. [B. rapa var. pekinensis), initiating several downstream signalling pathways for hormone regulation and the production of secondary metabolites and cell wall reinforcement.In an RNA-seq study of nfection . Similarnfection , which e, et al.  found anL. maculans, between compatible and incompatible interactions in B. napus cv. “Surpass 400” with either the virulent isolate UWA 192 or avirulent isolate UWAP11, showed the upregulation of enzymes involved in RuBisCO for CO2 fixation, H2O2 scavenging and redox metabolism [L. maculans-tolerant B. carinata, most of the proteins displayed antioxidant activities [B. carinata–L. maculans interaction, it was found from 2-DGE analysis that proteins related to ROS generation and photosynthetic enzymes were elevated in the resistant genotype 48 h after pathogen infection [B. rapa–P. brassicae pathosystem showed Rcr1 was associated with the ubiquitin-related proteasome system in plant defence reactions, along with the activation of the calcium-independent MAPK signalling pathway, regulation of ROS production via the activity of protein disulfide isomerases and upregulation of lignin biosynthesis [The use of 2D gel electrophoresis (2-DGE) and matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF/TOF MS) technology to study the proteomics of plant–pathogen interactions was first reported more than a decade ago . Comparatabolism . In L. mtivities . Similarnfection . A proteynthesis .B. oleracea–P. brassicae pathosystem to study protein expression during the early stages of host infection, with the highly expressed protein thioredoxin (TRX) enzyme identified, associated with oxidative stress and the pathogen defence response [P. brassicae-infected Chinese cabbage (B. rapa var. pekinensis) using isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic analysis were differentially up- or downregulated, and the proteins that contributed to the defence response included those involved in tryptophan and glutathione biosynthesis and cytokinin signalling [A high-throughput proteomic study using 2-DGE and MALDI-TOF/TOF MS analyses was performed in the response . More thgnalling .H. parasitica infection study in non-heading Chinese cabbage (B. campestris var. chinensis), a 2-DGE protein analysis and MALDI-TOF/TOF MS analysis along with transcript mRNA analysis using quantitative RT-PCR suggested a role for a Ca2+ signalling pathway as part of the ROS-mediated defence mechanism, with 39% of the genes having no correlation between protein and mRNA levels [In an A levels . StudiesA levels ,156. To A levels .B. juncea–Albugo candida successfully detected proteins that are differentially expressed in the resistant variety such as plant-thaumatin-like protein, superoxide dismutase, glutathione S-transferase, cysteine synthase and red chlorophyll catabolite reductase, suggesting ROS generation plays an important role in Brassica host resistance against this pathogen [Time-course protein profiling in the pathosystem of pathogen .Piriformospora indica, studying the beneficial effect of the fungal endophyte on the B. napus host, liquid chromatography-mass spectrometry (LC-MS), coupled with bioinformatics, highlighted significant levels of differentially expressed proteins involved in the stress/defence response during the cell-death colonisation phase in the plant roots, elucidating the role of P. indica in enhancing B. napus resistance against abiotic and biotic stresses [B. napus–P. indica host symbiont relationship. This could be done through the physical mapping of the genes on the B. napus genome assemblies supplemented with transcriptome data.In a proteomic study applied to a non-pathogenic, arbuscular mycorrhizal fungal species, stresses . There iBrassica are currently available, where long-read sequencing approaches such as ONT MinIon sequencing and PacBio sequencing were applied to assemble the genomes of L. maculans [S. sclerotiorum [A. brassicae [A. alternata [P. brassicae was assembled using Illumina Hiseq 2500 technology [A. candida genome was assembled using Roche/454 [Brassica pathogens revealed that the fungal pathogens contain high genomic variation, including mutations largely induced by transposable elements (TE), large-scale chromosomal re-arrangements [High-quality reference genome assemblies for the major pathogens of maculans , S. sclerotiorum , A. brasrassicae  and A. alternata . The genchnology , while toche/454 ; both arngements ,167, prengements  and the ngements ,170,171.ngements . The extngements .Brassica–pathogen interactions, as these omics resources are routinely applied in plant pathology research.The availability of these high-quality genome assemblies has greatly facilitated the discovery of candidate genes for effectors and virulence factors and significantly advanced our understanding about the pathogen in relation to its evolutionary pattern and species diversity through comparative and population genomics studies ,168,174.S. sclerotiorum towards B. napus. In the B. napus–L. maculans interaction, Haddadi, Larkan and Borhan [L. maculans effectors have been predicted from RNA-seq data, consistent with the results of Sonah, et al. [L. maculans lifestyle transition from a biotrophic to necrotrophic stage. This observation provides an additional clue in deciphering the arsenal of virulence mechanisms employed by L. maculans, one of the most notoriously adaptive disease-causing pathogens of the Brassica family. In Clubroot, small secreted proteins (SSPbPs) have been identified that were assumed to play critical functions in primary and secondary infections, leading to hypertrophic tissue development [X. campestris and P. carotovorum, a variety of mechanisms are deployed to evade host resistance including the release of extracellular enzymes such as cellulase, mannanase, pectinase, protease, polygalacturonases (PGs) and pectate lyase (Type II secretion system), the injection of effector proteins (Type III secretion system), as well as the production of exopolysaccharides and biofilm formation [Transcriptome analysis has been increasingly applied to study pathogen gene expression during host invasion, allowing the real-time monitoring of the molecular mechanisms involved in pathogenesis. The recent genome-wide transcriptome analysis of Chittem, et al.  highlighd Borhan  reported, et al. , who detelopment ,178. Forormation ,180,181.S. sclerotiorum, 80 putative secondary metabolite gene clusters implicated in virulence in B. napus were identified in sub-telomeric regions close to transposable elements, with the upregulation of 12 polyketide synthases (PKSs) and enzymes during S. sclerotiorum infection of B. napus, revealing clues about the virulence pathway in the B. napus host [S. sclerotiorum to suppress host defence mechanisms, such as PKS, nonribosomal peptide synthase (NRPS) and chalcone synthase (CHS), were upregulated in an RNA-seq experiment studying B. napus–S. sclerotiorum disease resistance [Through the in silico analysis of comparative genomic and transcriptomic data of pus host . Enzymessistance .The fungal plant pathogen secretes a whole suite of proteins, collectively known as the secretome, during its interaction with the host . The secBrassica–pathogen interactions to support breeding resistant Brassica varieties [An understanding of the structural features of effector proteins, the diversity of the effector genes, and how these genes play a role in the pathogenicity and the evolutionary patterns of the genes are important for uncovering the complexity of the resistance mechanism in arieties . Due to arieties ,188, Sigarieties  and Apoparieties . Bioinfoarieties . Besidesarieties .The conventional secretion pathway for the proteins during plant–pathogen interaction involves the endoplasmic reticulum–Golgi pathway ,194. HowBrassica, oxylipins were found to display fungicidal activity against A. brassicae, L. maculans, S. sclerotiorum and Verticillium longisporum [F. oxysporum hijacking the oxylipin JA signalling pathway in A. thaliana [Some signalling molecules produced by phytopathogenic fungal species that play a part in virulence resemble homologous signalling molecules in the host, acting as mimics to evade the plant immune system for successful disease development . For insgisporum . In phytgisporum ,201, an thaliana .P. brassicae Pb3 genome assembly revealed that the pathogen contains genes that are associated with the biosynthesis of the plant hormones cytokinin and auxin, suggesting a potential role for these hormones in virulence activity in the host plant [L. maculans, suggesting a putative role of ABA production in disease progression in B. napus [P. brassicae is the benzoic acid (BA)/SA methyltransferase protein (PbBSMT), which suppresses host SA signalling during plant defence [PbBSMT is similar to that of the SABATH methyltransferase gene family in A. thaliana, AtBSMT1, where the genes play a role in converting SA into methyl salicylate (MeSA), which is the inactive form of SA, thereby compromising the SAR defence response [P. brassicae infection in Kohlrabi (B. oleracea var. gongylodes) showed that PbBSMT was one of the highest-expressed pathogen genes in the root gall tissue, playing a role in the local reduction of SA via PbBMST-mediated methylation [AtBSMT1 vs. PbBSMT in P. brassicae-infected Arabidopsis (host) and A. candida-infected Arabidopsis (non-host), comparing the level of SA inactivation in Arabidopsis, that PbBSMT resulted in higher levels of SA inactivation, meaning PbBSMT suppressed the host and non-host SAR defence mechanisms at a greater level [The gene expression profile from the st plant , while gB. napus . One of  defence . The funresponse . A transhylation . It was er level ,207. Muler level .B. napus have been shown to inhibit the growth of X. campestris, S. sclerotiorum and L. maculans, thus acting as natural biological control against B. napus diseases [B. juncea var. tumida) and P. brassicae-infected roots of the same plant species showed a more diverse composition of the fungal endophytes in the healthy roots compared to in the diseased roots. This suggests a strong interaction network in the fungal endophyte community that contributes towards the optimum health of the host plant [B. napus from pathogen invasion.Beneficial bacterial endophytes found in the apoplast region of diseases . The higst plant . A combiBrassica crops is crucial for the identification of disease resistance targets. A web-based database called the Pathogen-Host Interactions database (PHI-base) has been set up that stores curated experimental data obtained from host–pathogen studies, encompassing phenotypic data and biological data on pathogenicity, virulence, and effector gene functions from fungal, oomycete and bacterial pathogens from animal, plant, fungal and insect host species, with embedded search links including BLAST, PubMed, UniProt Knowledgebase and others [Interactomics is the study of networks of gene and protein interactions in biological systems . Understd others . Complemd others .B. oleracea were identified using liquid chromatography-quadrupole time-of-flight (LC-QTOF)-based metabolite profiling, which revealed that metabolic changes in the host occurred 48 h after infection and implicated photosynthesis, alkaloids, coumarins and sphingolipids as involved during the infection process [Brassica–Alternaria pathophysiology to identify important elements in the regulation of resistance mechanisms and to pinpoint molecular targets for engineering enhanced resistance in Brassica crops [Metabolomics in plant pathology refers to the study of host plant metabolism changes in response to pathogen infection that provides an understanding of how host–pathogen interaction, through a (de)activation of metabolites and associated signalling pathways, could lead towards a resistant or susceptible outcome for the host . Metabol process . Systemsca crops .A. thaliana–S. sclerotiorum pathosystem, where a genome-scale metabolic model of S. sclerotiorum based on global gene expression was constructed to assess the metabolic activity in different parts of the hyphal cells, supporting the hypothesis that cooperation in S. sclerotiorum hyphal cells is necessary for virulence and host colonisation [B. napus resistance response against Clubroot and the underlying QTL controlling the trait on chromosome C03 and C09 [Brassica species [S. sclerotiorum pathosystem, where the induction of JA signalling, elevated ROS control and reprogramming of the phenylpropanoid pathway have been suggested to be an important resistance mechanism [Brassica pathosystems could be discovered through the application of multi-omics technologies -Cas9 (CRISPR-associated protein 9) system. In B. napus, two genes, BnWRKY11 and BnWRKY70, that encode for WRKY transcription factors were successfully knocked out using CRISPR-Cas9, showing the latter gene regulates disease resistance to S. sclerotiorum [Brassica that contain many copies of the same genes as homeologs within the genome. The CRISPR-Cas9 system was also successfully applied in B. rapa for early-flowering trait genome editing [L. maculans, the chitin-binding gene LmCBP1, which was highly expressed during infection in B. napus and functional analysis using CRISPR-Cas9, was shown to play a role in enhancing cell death for pathogen growth and also to be involved in tolerance towards H2O2 during the plant immune response [Functional analysis of candidate genes in the rotiorum . This mu editing . In L. mresponse .Brassica–pathogen interactions in many ways and will become the mainstream approach to rapidly identifying QTL/candidate R/pathogenicity genes for breeding superior Brassica crop species that are resistant towards the main pathogen types discussed in this review. Using the various omics or multi-omics tools, supplemented with further fine tuning of the bioinformatics methods, will not only speed up the screening of favourable alleles in Brassica germplasm promoting resistance against the major pathogens, but also expediate the identification and cloning of favourable genes with increased precision. Together, this will foster success in the breeding of improved and/or new varieties of Brassica crops for sustainable agriculture [The omics tools have advanced our understanding of iculture .


Mycobacterium tuberculosis re-infection or TB recrudescence following successful cure. We also discuss immune pathways whereby the gut microbiome could impact TB disease and serve as target for clinical manipulation.Although tuberculosis (TB) is a curable disease, it remains the foremost cause of death from a single pathogen. Globally, approximately 1.6 million people died of TB in 2017. Many predisposing factors related to host immunity, genetics and the environment have been linked to TB. However, recent evidence suggests a relationship between dysbiosis in the gut microbiome and TB disease development. The underlying mechanism(s) whereby dysbiosis in the gut microbiota may impact the different stages in TB disease progression, are, however, not fully explained. In the wake of recently emerging literature, the gut microbiome could represent a potential modifiable host factor to improve TB immunity and treatment response. Herein, we summarize early data detailing (1) possible association between gut microbiome dysbiosis and TB (2) the potential for the use of microbiota biosignatures to discriminate active TB disease from healthy individuals (3) the adverse effect of protracted anti-TB antibiotics treatment on gut microbiota balance, and possible link to increased susceptibility to  Mycobacterium tuberculosis (M.tb). TB is spread when infectious aerosol droplets containing the bacilli are released from an infected individual, typically through sneezing or coughing [M.tb will progress to active TB disease during their lifetime, approximately 1.6 million people died of the disease in 2017 alone [M.tb infection, leading to increased susceptibility or recurrence of TB disease [Tuberculosis (TB) is an infectious disease caused by the non-motile, acid fast bacillus coughing . Althoug17 alone . It is k17 alone . Typical17 alone . Recent  disease . In thisM.tb infection. However, these alterations were minimal and were mainly observed in the comparative abundance of species within the genus Bacteroides [Bacteroides increased in abundance during anti-TB antibiotics treatment, including Bacteroides fragilis, whereas, the population of members within the Clostridiales order, declined significantly [Erysipelatoclostridium, Fusobacterium and Prevotella, whereas, depletion of Blautia, Lactobacillus, Coprococcus, Ruminococcus and Bifidobacterium was observed in comparison to the latent TB group. Furthermore, after more than 1 year of stopping treatment, the intestinal microbiome of the individuals cured of TB (through 6 months anti-TB drug treatment), was clearly distinguishable from the latent TB cohorts, indicating that treatment for TB has a long-lasting effect on microbiome composition [M.tb strain caused distinct changes in the diversity of the gut microbiome especially in the order Clostridiales. Furthermore, many genera within the class Clostridia such as Ruminococcus, Butyricicoccus, Acetivibrio, Alkaliphilus and Peptococcus declined in their relative population during treatment. Interestingly, only the gut composition of members of the genus Erysipelatoclostridium increased during treatment [Many studies investigating perturbations in the gut microbiome during TB disease and the profound effect of anti-TB drug therapy on the gut microbiome composition are currently emerging. A recent study reported a decline in the alpha diversity of the gut microbiome after pulmonary teroides . In contficantly . An earlficantly . Howeverficantly . Individposition . The resreatment .Lachnospira and Prevotella in individuals newly diagnosed with active TB and in those presenting with recurrent TB [M.tb mRNA was detected in bronchoalveolar lavage and sputum samples collected from these patients, with TB disease recurring in some of the patients within 2 years from treatment completion and presumed cure [In another study, the gut microbiome composition of individuals presenting with recurrent TB (previously declared as cured) contrasted with those of healthy controls . Microbirrent TB . The autrrent TB . These rmed cure .M.tb, recent literature have taken into account the profound gut microbiome dysbiosis induced by anti-TB drug therapy [M.tb are scarce.Although anti-TB antibiotics are effective in killing  therapy –8. Where therapy . A worri therapy  which shM.tb despite protracted anti-TB antibiotics treatment. The study showed that treating mice with a combination of isoniazid and pyrazinamide or rifampicin alone, significantly altered the gut microbiome. Isoniazid/pyrazinamide treatment expanded the abundance of Bacteroidetes. Whereas, rifampicin depleted Firmicutes population while increasing the abundance of Verrucomicrobia and Bacteroidetes phyla. At the genus, differences in Clostridia IV and XIV clusters were the most noteworthy change in the isoniazid/pyrazinamide-treated animals. Interestingly, dysbiosis in gut microbiome resulting from treating these mice with isoniazid/pyrazinamide as opposed to rifampicin led to an increase in M.tb load [M.tb growth. In addition, the production of interleukin (IL)-1-beta (β) and tumor necrosis factor-alpha (TNF-α), together with the expression of major histocompatibility complex class II (MHCII) significantly declined after M.tb infection [In a recent study, Khan et al.  began to.tb load . Further.tb load . Alveolanfection .M.tb-infected alveolar macrophages from the isoniazid/pyrazinamide-treated animals significantly increased M.tb load in recipient mice [M.tb. By interpreting these data we could infer that upon successful TB treatment and cure (1) gut microbiome community is perturbed (2) this gut microbiota dysbiosis impact negatively on macrophage metabolism (3) as a result macrophage mycobactericidal activity is impaired upon subsequently M.tb infectious challenge, leading to successful re-infection (4) balance in gut microbiome composition is vital to sustain alveolar macrophage response against M.tb. However, studies detailing these associations are only emerging and would require further validation. Future studies could investigate the involvement of other functional and phenotypic immune markers. In addition, such studies may include compositional and functional analysis of gut microbiota metabolites, e.g., short chain fatty acids (SCFAs) in peripheral circulation during anti-TB antibiotics treatment.Another striking finding from the study was that adoptive transfer of ent mice . How thient mice , 12. AltRuminococcus obeum, Bifidobacterium longum, Roseburia intestinalis, Roseburia inulinivorans, Coprococcus comes, Akkermansia muciniphila, Eubacterium rectale, Bifidobacterium adolescentis and Roseburia hominis [Recently, there has been an intensified search for biomarker signatures that could accurately diagnose TB, predict progression from latent to active TB, assist in monitoring the response to anti-TB therapy and prediction of treatment outcome. In the wake of emerging literature on gut microbiota dysbiosis associated with TB and anti-TB drug treatment, developing gut microbiota biosignatures for TB disease and treatment response could be a promising area for investigation. Hu et al.  in a rec hominis . In addiBesides strengthening the integrity of intestinal epithelial cells, SCFAs play an important role in inflammatory responses in the gut and at distal mucosal sites such as the respiratory tract , 15. ManRoseburia hominis, Roseburia inulinivorans and Hemophilus parainfluenzae were selected after five repeated experiments and cross validation using a training set consisting of 31 healthy controls and 30 TB patients [Bacteroides vulgatus identified 46 SNPs that were differentially distributed between the two groups. In a related earlier study, an increase in gut microbiota that produces butyrate was reported in TB patients when compared to close household contact as healthy controls [Eubacterium rectale, Faecalibacterium prausnitzii, and Roseburia inulinivorans [Notably, Hu et al.’s  study depatients . The arepatients . In addicontrols . These gnivorans . Taken tClostridium sporogenes produce indole-3-propionic acid (IPA) from the metabolism of tryptophan. IPA readily percolates gut barrier and accumulate in human circulation [M.tb burden in a mouse model and the molecule was well tolerated showing adequate pharmacokinetic properties [M.tb [Commensal microbiota regulates both adaptive and innate immunity directly or indirectly by producing small molecules (metabolites) which influence the threshold of immune activation following pathogen stimulations. In line with this role, although epithelial cell barrier supposedly restricts microbes to the gut, microbial metabolites can infiltrate epithelial cell boundary. These metabolites then aggregate in host circulation and are sensed by circulating immune cells . Therefoculation . In one operties . Althouges [M.tb .Bacteroides fragilis strains that produced polysaccharide-A (PSA). This CD4 + T cell proliferation restored balance between Th (T helper)-1 versus Th2 cytokines by increasing IFN-γ and TNF-α production in the germ-free mice [Clostridia strains [Indeed, specific gut microbiota species have been shown to induce different immunological phenotypes or cytokine responses, which may influence disease pathogenesis or pathology . For exaree mice . Similar strains .M.tb requires a coordinated and balanced expression of pro-and anti- inflammatory T cell subsets and regulatory T cell phenotypes. Early evidence suggests that the gut microbiota may be critical for maintaining this balance. For instance, Dumas et al. [M.tb was prompted by antibiotics-induced alterations in the diversity of the gut microbiome. On one hand, there was no substantial change in the recruitment of neutrophils, macrophages, and dendritic cells to the lungs between the untreated and antibiotics-treated mice. Furthermore, production of the pro-inflammatory cytokines, IFN-γ, TNF-α and IL-1β, remained unchanged in the antibiotics-treated animals [M.tb infection [In addition to innate immune responses, elimination or control of s et al.  reported animals . Howevernfection . AdditioM.tb [M.tb is also increasingly being recognized [M.tb colonization [IL-17 secretion is associated with increased recruitment of neutrophils, and optimal Th1 cell inflammatory responses , 32. IL-M.tb . In addiM.tb . The rolcognized –37. DumaM.tb-infected animals compromised mouse immunity and increased the ability of the pathogen to spread to other organs [M.tb, with Tregs expanding in numbers while IFN-γ and TNF-α- producing Th1 cells diminished in their frequencies. Strikingly, after fecal transplant, TB immunity was reestablished and the spread of M.tb to different organs was prevented [In a similar study, antibiotic-induced changes in the gut diversity of r organs . This direvented . In a hurevented . The numrevented . The autrevented .M.tb and granuloma formation, although they play a controversial role during TB disease. While some studies associate the abundance of neutrophils to protection against TB, others have suggested that disease progression is associated with the accumulation of neutrophils [M.tb and M. bovis BCG [M.tb CFUs following infection [M.tb resistance is a question that requires further investigation.Neutrophils form an integral part of the early immune response to trophils –42. It itrophils . In the ovis BCG . Sugawarnfection . Furthernfection . NeverthM.tb, are pre-polarized by responses generated against other infections, including gut microbiota-associated infections. For example, infection by Helicobacter hepaticus significantly influenced TB subunit-vaccine-induced protection through an IL-10 dependent pathway [H. hepaticus infection increased colonic IL-10 mRNA expression and mice susceptibility following M.tb challenge [H. hepaticus-infected mice resulted in reduced protection against M.tb. Nevertheless, the protective impact of the subunit vaccine was reestablished following treatment with anti-IL-10 receptor antibody [Helicobacter pylori infection were less likely to progress from latent to active TB when compared to H. pylori seronegative individuals. This was due to enhanced Th1 responses to TB antigens, and the outcome was the same even in individuals concurrently harbouring helminth infections [Helicobacter species and the immune response in the gut. Important questions arising from these studies include; (1) how an unhealthy gut microbiome could be manipulated to restore its positive immune-response modulating effects on TB immunity, (2) the specific pathways implicated in the translation of the immune responses generated in the gut to protective lung immunity, (3) which specific microbiome species or cocktail of gut microbiota promote the expansion of immune cell phenotypes with specific roles in limiting TB disease. A summary of recent literature on gut microbiome and TB is provided in Table Another consideration is that immune cells mounting a challenge against infection by  pathway . H. hepahallenge . In addiantibody . In a sifections . This imfections . ReportsM.tb infection [Bifidobacterium and Lactobacillus with neomycin was associated with altered immune response to influenza A virus infection with concomitant increase in lung damage in a mouse model [Bifidobacterium probiotic reconstitution of the gut microbiota, TLR7 response improved and restored the production of IFN-γ and IL-17 but remarkably inhibited IL-4 and IL-10 induction [Bacterial peptidoglycan, polysaccharide, lipoteichoic acid and lipopolysaccharide (LPS) are known to stimulate toll-like receptor (TLR) signaling . In addinfection . Furthernfection . For exanfection . A studynfection  showed tse model . This annduction . Lung danduction . These dM.tb infection, we could hypothesize that in a microbiota balance state, different gut commensal bacteria and metabolites provide signals that educate innate and adaptive immune cells while inducing both pro- and anti-inflammatory cell types. This implies that in addition to local immune defense, immune signals generated by gut microbiota will contribute to the pool of lymphocytes recruited to the airways upon M.tb infectious challenge. Therefore, heterogeneity in the immune response ensures a homeostatic lung cytokine environment  is altered by binding of H. pylori [Gut microbiota play a role in the pharmacokinetics (PK) of drugs. Although the synthesis of primary bile acids and metabolism of drugs essentially occurs in the liver, secondary bile acids are mostly produced by the gut microbiota . In addi. pylori , 63.M.tb strains resulting from exposure to lower than therapeutic dose [M.tb-infected mice treated with anti-TB antibiotics while simultaneously receiving faecal transplant from normal mice, and compare with antibiotics-treatment only controls (2) compare anti-TB drug PK in M.tb-infected germ-free mice vs conventionally colonized mice.One common cause of treatment failure during TB therapy is the selection of resistant tic dose , 65. Widtic dose , 67. Amotic dose , 69. IntBacteroides species [B. fragilis gavage, inoculation with B. fragilis polysaccharides, or by adoptive immunotherapy with B. fragilis-specific murine T cells [Bacteroides thetaiotaomicron, while Faecalibacterium and Clostridiales enriched gut microbiota-favoured treatment efficacy [Bifidobacterium and anti-PD-L1 monoclonal antibody treatment improved tumor control in mice when compared to the immunotherapeutic intervention alone in another study [Faecalibacterium prausnitzii [Faecalibacterium prausnitzii is a butyrate-producing microbiota. Accordingly, the authors opined that tacrolimus drug metabolism could be connected to butyrate availability. These reports demonstrate that commensal microbiota could be manipulated for clinical advantage. This methodology could be explored during TB treatment using probiotics directed not at cure, but to dampen the effect of anti-TB antibiotics on gut microbiota community.In the case of the cancer-targeting drug ipilimumab , the effectiveness of the drug was shown to be reliant on specific  species . In this T cells . This unefficacy . Similarer study . Likewiser study . As the usnitzii . FaecaliM.tb infection or response to TB drug treatment are still emerging. Equally important is establishing whether gut microbiome dysbiosis induced by the protracted anti-TB antibiotics treatment is linked to increased susceptibility to M.tb re-infection or TB recrudescence after successful cure. This could change the way TB disease is currently treated and may translate into the development of new therapeutic approaches. Future directions may include:Development of microbiota signatures that discriminate between the different stages in the life cycle of TB disease. Such studies may include a large cohort of participants from different geographical settings.Investigating the impact of alterations in specific gut microbiota species on TB susceptibility and the immune cells/mechanisms involved.Metabolomic and functional characterization of peripheral pool of metabolites produced by gut microbiota during the different stages of TB disease.More studies investigating anti-TB drug-induced gut microbiome dysbiosis and the potential impact on susceptibility to re-infection, together with the associated immune cells and pathways affected.Establishing whether dysbiosis induced by anti-TB drugs themselves following protracted use impact on the drug PK.Developing animal models to explore whether anti-TB antibiotics treatment combined with probiotics  will improve treatment response and outcome.Reports investigating whether alterations in the gut microbiome contribute to bias in inter-individual levels of susceptibility to