Reconstruction of Transcription Control Networks in Mollicutes by High-Throughput Identification of Promoters

Bacteria of the class Mollicutes have significantly reduced genomes and gene expression control systems. They are also efficient pathogens that can colonize a broad range of hosts including plants and animals. Despite their simplicity, Mollicutes demonstrate complex transcriptional responses to various conditions, which contradicts their reduction in gene expression regulation mechanisms. We analyzed the conservation and distribution of transcription regulators across the 50 Mollicutes species. The majority of the transcription factors regulate transport and metabolism, and there are four transcription factors that demonstrate significant conservation across the analyzed bacteria. These factors include repressors of chaperone HrcA, cell cycle regulator MraZ and two regulators with unclear function from the WhiA and YebC/PmpR families. We then used three representative species of the major clades of Mollicutes (Acholeplasma laidlawii, Spiroplasma melliferum and Mycoplasma gallisepticum) to perform promoters mapping and activity quantitation. We revealed that Mollicutes evolved towards a promoter architecture simplification that correlates with a diminishing role of transcription regulation and an increase in transcriptional noise. Using the identified operons structure and a comparative genomics approach, we reconstructed the transcription control networks for these three species. The organization of the networks reflects the adaptation of bacteria to specific conditions and hosts

Gene Silencing through CRISPR Interference in Mycoplasmas

Mycoplasmas are pathogenic, genome-reduced bacteria. The development of such fields of science as system and synthetic biology is closely associated with them. Despite intensive research of different representatives of this genus, genetic manipulations remain challenging in mycoplasmas. Here we demonstrate a single-plasmid transposon-based CRISPRi system for the repression of gene expression in mycoplasmas. We show that selected expression determinants provide a level of dCas9 that does not lead to a significant slow-down of mycoplasma growth. For the first time we describe the proteomic response of genome-reduced bacteria to the expression of exogenous dcas9. The functionality of the resulting vector is confirmed by targeting the three genes coding transcription factors-fur, essential spxA, whiA, and histone-like protein hup1 in Mycoplasma gallisepticum. As a result, the expression level of each gene was decreased tenfold and influenced the mRNA level of predicted targets of transcription factors. To illustrate the versatility of this vector, we performed a knockdown of metabolic genes in a representative member of another cluster of the Mycoplasma genus-Mycoplasma hominis. The developed CRISPRi system is a powerful tool to discover the functioning of genes that are essential, decipher regulatory networks and that can help to identify novel drug targets to control Mycoplasma infections

The efficiency of <i>camR</i> insertion into wild-type <i>M</i>. <i>gallisepticum</i>, ΔS.MgaS6I strain, and four strains with <i>tetM</i> insertion in various intergenic regions.

CFUs of strains with significant difference, as compared to the CFU of ΔS.MgaS6I strain (Student’s t-test, P<0.05), have been indicated using asterisks.</p

Fig 8 -

A–Difference between the expression levels of paired genes for mutants with EGFP genes under synthetic promoters, with or without methylation sites. For each pair, the difference for EGFP gene in comparison with control genes eno, gadp, tuf, ligA, and gyrB is shown. Genes with significant difference between promoters with or without the methylation site (Student’s t-test, Benjamini–Hochberg correction, PEGFP promoters with or without methylated sites in -10 box, -35 box, between -35 and -10 boxes, and in the TSS. Methylation sites are underlined; methylated adenines in forward and reverse strands are in bold; -10 boxes are in blue and highlighted with blue boxes; -35 boxes are highlighted with green boxes and the sequence with strong consensus to the -35 box is in green; TSSs are in red and marked with red arrows; sequence differences between paired methylated or non-methylated promoters are in pink.</p

Methylated fraction of each methylation site.

A–Number of sites with different fractions of methylation. Colors represent sites located in one of the four parts of the genome: between the origin and midpoint of the chromosome, on the plus or minus strand. The panel on the right schematically shows the methylation sites that were counted in each group. B–Number of sites with different fractions of methylation. In this figure, the location of sites in the genome has not been considered. Colors represent the sites on the ANCNNNNCCT or AGGNNNNGNT strands in the double-stranded methylation motif. The panel on the right schematically shows the methylation sites that were counted in each group.</p

Characteristics of the modification motif ANCNNNNCCT.

Mean Score–mean Modification QV of instances of this motif that were detected as modified; Mean IPD Ratio–mean interpulse duration (IPD) ratio of instances of this motif that were detected as modified; Mean Coverage–mean coverage of instances of this motif that were detected as modified.</p

Distribution of DNA modification sites along the genome of <i>M</i>. <i>gallisepticum</i> S6.

A–Annotated features: RM systems are in orange, vlhA clusters in green, the CRISPR system in grey, the virulence cluster in blue, and mobile elements in black. B and С –Whole-genome representation of the DNA modification motif ANCNNNNCCT for plus and minus strand, respectively. The lines indicate positions of sites, and the colors from red to blue represent percentage of methylation in each site. Percentage of methylation was calculated using the build-in SMRT protocol, as the fraction of reads aligning to the position that has a modified base. D–Density of methylation sites. Maximum density of methylation is highlighted in orange, while minimum is highlighted in green. E–GC content. Maximum GC content is highlighted in red, while minimum is highlighted in blue. F–Hypo-methylated sites are in green, hemi-methylated sites in orange and blue (for plus and minus strands, respectively); proteins with differential abundance (as assessed using 2D-DIGE) between WT and ΔS.MgaS6I strains are in grey.</p

Comparison of the proteomic profiles of the wild-type <i>M</i>. <i>gallisepticum</i> (red) and the ΔS.MgaS6I strain (green) with unmethylated DNA.

Proteins, whose abundances reproducibly changed in all the studied strains with tetM insertion in the various genomic regions, as compared to that in the WT, are in blue, while differences that are unique to ΔS.MgaS6I are in white.</p

Phylogenetic tree of TRDs of specificity subunits of <i>M</i>. <i>gallisepticum</i> S6 and other TRDs with similar specificity.

The names in the leaves represent the TRD names, which consist of the REBASE name of the HsdS and its sequence specificity. The numbers on the nodes are distance measures calculated using BLOSUM62 substitution matrices.</p