Transcriptional profiling and mRNA stability – don’t shoot the messenger David R. Sherman Seattle Biomedical Research Institute Grand Challenge of Latent TB Mtg. Cape Town February 25, 2012

Landscape of TB latency CONFIDENTIAL 4.4 billion PPD(-) 1.8 billion PPD(+) 16 million active infections 1.5 million deaths

Landscape of TB latency CONFIDENTIAL 4.4 billion PPD(-) 1.8 billion PPD(+) 16 million active infections 1.5 million deaths Calcified lesions Few viable bacteria Caseous lesions Low numbers of bacteria Evolving lesions Bacterial replication Latency to Disease Active disease

Landscape of TB latency CONFIDENTIAL 4.4 billion PPD(-) 1.8 billion PPD(+) 16 million active infections 1.5 million deaths Calcified lesions Few viable bacteria Caseous lesions Low numbers of bacteria Evolving lesions Bacterial replication Latency to Disease Active disease GC-11

Using gene expression to probe latent TB Concept – TB gene expression in vivo will reveal the conditions that it experiences. - Physiology - Drug targets Infected tissue Gene regulatory network

Using gene expression to probe latent TB Infected tissue Gene regulatory network Assumes TF binding = Tx initiation = mRNA abundance

mRNA abundance balance Shalem et al Transcription Rate Degradation Rate

Talk outline Characterize MTB mRNA decay – Global mRNA half life (T 1/2 ) – Most stable/labile messages – Factors affecting stability mRNA decay in stress response – Mild cold shock – Hypoxia Summary

Measuring mRNA degradation Rifampicin Log Phase RNA Cy dye label Microarray Custom array design: 100,000 TB oligos 30,000 control oligos

T0 T20 T5T10 T15 mRNA decay by microarray

Individual decay curve Rifampicin (rif)

Individual decay curve Rifampicin (rif) T 1/2

Data filtered for reproducibility and R 2 Inclusion criteria: – T 1/2 with R 2 >0.7 – Starting [RNA] > 4x background – Valid measures at > half replicates 2139 genes met criteria

TB mRNA is very stable Average MTB T 1/2 = 9.5 minutes

TB mRNA is very stable

Functional Category Mean half-life (minutes) information pathways8.7 * virulence, detoxification, and adaptation9.3 lipid metabolism9.4 cell wall and cell processes9.4 metabolism and respiration9.5 hypothetical protein9.6 Regulatory proteins9.6 insertion seqs and phages10.4 ** PE/PPE11.1 ** *=significantly lower **=significantly higher mRNA T 1/2 by functional category

Functional subcategory Specified Gene % Whole Genome % P Value Functional Enrichment for the genes with the shortest 1/2 life Posttranslational modification, protein turnover, chaperones Translation, ribosomal structure and biogenesis Energy production and conversion Intracellular trafficking, secretion, and vesicular transport Functional Enrichment for the genes with the longest 1/2 life Replication, recombination and repair Amino acid transport and metabolism PE/PPE Energy production and conversion

Physical characteristics and mRNA stability

mRNA abundance and stability R 2 = 0.8

mRNA abundance and stability Inherent to the mRNA? Inherent to abundance? Test: DosR regulon: ~48 genes induced by hypoxia, etc. Place dosR under tet control. Induce regulon in log phase

Induced transcripts degrade faster >2000 transcripts did not change stability

Modified mRNA decay in response to stress conditions Are specific transcripts (de)stabilized? Does the global mRNA ½ life change? Is mRNA decay regulated to change transcript abundance? Temperature Hypoxia

mRNA degradation at 20C After 5 hrs: Only 55 genes decayed 2x or more. Degradation not measurable. T 1/2 very sensitive to temp. T = 5 hrs

mRNA stability in hypoxia Rifampicin Log Phase Hypoxia 120+ RNA Cy dye label Microarray

mRNA stability in altered O 2

MTB mRNA decay characterization Reliable mRNA half lives for >2000 genes. Average half life ~9.5 minutes. Half life inversely correlated with transcript concentration. Transcripts stabilized by cold, hypooxia.

Questions to explore Why is TB mRNA very stable? – RNases or mRNA secondary structure? Hypoxia and low temp: Transcription decreased to balance decay? Mechanism? How to repress genes? What are the consequences? – Systems modeling

Thank you! Kyle Minch Tige Rustad Debbie Whitley Bill Brabant Jessica Winkler Paul G Allen Family Foundation Bill and Melinda Gates Foundation NIAID contract # HHSN C

Rifampicin is stopping transcription No rif induced genes Lux assay to look for induction after rif treatment – Hypoxia sensitive promoter driving lux Total degradation by array