Debugging and consolidating multiple synthetic chromosomes reveals combinatorial genetic interactions.

The Sc2.0 project is building a eukaryotic synthetic genome from scratch. A major milestone has been achieved with all individual Sc2.0 chromosomes assembled. Here, we describe the consolidation of multiple synthetic chromosomes using advanced endoreduplication intercrossing with tRNA expression cassettes to generate a strain with 6.5 synthetic chromosomes. The 3D chromosome organization and transcript isoform profiles were evaluated using Hi-C and long-read direct RNA sequencing. We developed CRISPR Directed Biallelic URA3-assisted Genome Scan, or "CRISPR D-BUGS," to map phenotypic variants caused by specific designer modifications, known as "bugs." We first fine-mapped a bug in synthetic chromosome II (synII) and then discovered a combinatorial interaction associated with synIII and synX, revealing an unexpected genetic interaction that links transcriptional regulation, inositol metabolism, and tRNASerCGA abundance. Finally, to expedite consolidation, we employed chromosome substitution to incorporate the largest chromosome (synIV), thereby consolidating >50% of the Sc2.0 genome in one strain.

An expanded universe of cancer targets.

The characterization of cancer genomes has provided insight into somatically altered genes across tumors, transformed our understanding of cancer biology, and enabled tailoring of therapeutic strategies. However, the function of most cancer alleles remains mysterious, and many cancer features transcend their genomes. Consequently, tumor genomic characterization does not influence therapy for most patients. Approaches to understand the function and circuitry of cancer genes provide complementary approaches to elucidate both oncogene and non-oncogene dependencies. Emerging work indicates that the diversity of therapeutic targets engendered by non-oncogene dependencies is much larger than the list of recurrently mutated genes. Here we describe a framework for this expanded list of cancer targets, providing novel opportunities for clinical translation.

Synthetic Genomes.

DNA synthesis technology has progressed to the point that it is now practical to synthesize entire genomes. Quite a variety of methods have been developed, first to synthesize single genes but ultimately to massively edit or write from scratch entire genomes. Synthetic genomes can essentially be clones of native sequences, but this approach does not teach us much new biology. The ability to endow genomes with novel properties offers special promise for addressing questions not easily approachable with conventional gene-at-a-time methods. These include questions about evolution and about how genomes are fundamentally wired informationally, metabolically, and genetically. The techniques and technologies relating to how to design, build, and deliver big DNA at the genome scale are reviewed here. A fuller understanding of these principles may someday lead to the ability to truly design genomes from scratch.

Manipulating the 3D organization of the largest synthetic yeast chromosome.

Whether synthetic genomes can power life has attracted broad interest in the synthetic biology field. Here, we report de novo synthesis of the largest eukaryotic chromosome thus far, synIV, a 1,454,621-bp yeast chromosome resulting from extensive genome streamlining and modification. We developed megachunk assembly combined with a hierarchical integration strategy, which significantly increased the accuracy and flexibility of synthetic chromosome construction. Besides the drastic sequence changes, we further manipulated the 3D structure of synIV to explore spatial gene regulation. Surprisingly, we found few gene expression changes, suggesting that positioning inside the yeast nucleoplasm plays a minor role in gene regulation. Lastly, we tethered synIV to the inner nuclear membrane via its hundreds of loxPsym sites and observed transcriptional repression of the entire chromosome, demonstrating chromosome-wide transcription manipulation without changing the DNA sequences. Our manipulation of the spatial structure of synIV sheds light on higher-order architectural design of the synthetic genomes.

Pervasive RNA folding is crucial for narnavirus genome maintenance.

A synthetic biology approach toward constructing an RNA-based genome expands our understanding of living things and opens avenues for technological advancement. For the precise design of an artificial RNA replicon either from scratch or based on a natural RNA replicon, understanding structure-function relationships of RNA sequences is critical. However, our knowledge remains limited to a few particular structural elements intensively studied so far. Here, we conducted a series of site-directed mutagenesis studies of yeast narnaviruses ScNV20S and ScNV23S, perhaps the simplest natural autonomous RNA replicons, to identify RNA elements required for maintenance and replication. RNA structure disruption corresponding to various portions of the entire narnavirus genome suggests that pervasive RNA folding, in addition to the precise secondary structure of genome termini, is essential for maintenance of the RNA replicon in vivo. Computational RNA structure analyses suggest that this scenario likely applies to other "narna-like" viruses. This finding implies selective pressure on these simplest autonomous natural RNA replicons to fold into a unique structure that acquires both thermodynamic and biological stability. We propose the importance of pervasive RNA folding for the design of RNA replicons that could serve as a platform for in vivo continuous evolution as well as an interesting model to study the origin of life.

Prioritizing drug targets by perturbing biological network response functions.

Therapeutic interventions are designed to perturb the function of a biological system. However, there are many types of proteins that cannot be targeted with conventional small molecule drugs. Accordingly, many identified gene-regulatory drivers and downstream effectors are currently undruggable. Drivers and effectors are often connected by druggable signaling and regulatory intermediates. Methods to identify druggable intermediates therefore have general value in expanding the set of targets available for hypothesis-driven validation. Here we identify and prioritize potential druggable intermediates by developing a network perturbation theory, termed NetPert, for response functions of biological networks. Dynamics are defined by a network structure in which vertices represent genes and proteins, and edges represent gene-regulatory interactions and protein-protein interactions. Perturbation theory for network dynamics prioritizes targets that interfere with signaling from driver to response genes. Applications to organoid models for metastatic breast cancer demonstrate the ability of this mathematical framework to identify and prioritize druggable intermediates. While the short-time limit of the perturbation theory resembles betweenness centrality, NetPert is superior in generating target rankings that correlate with previous wet-lab assays and are more robust to incomplete or noisy network data. NetPert also performs better than a related graph diffusion approach. Wet-lab assays demonstrate that drugs for targets identified by NetPert, including targets that are not themselves differentially expressed, are active in suppressing additional metastatic phenotypes.

E-cadherin is required for metastasis in multiple models of breast cancer.

Metastasis is the major driver of death in patients with cancer. Invasion of surrounding tissues and metastasis have been proposed to initiate following loss of the intercellular adhesion protein, E-cadherin1,2, on the basis of inverse correlations between in vitro migration and E-cadherin levels3. However, this hypothesis is inconsistent with the observation that most breast cancers are invasive ductal carcinomas and express E-cadherin in primary tumours and metastases4. To resolve this discrepancy, we tested the genetic requirement for E-cadherin in metastasis using mouse and human models of both luminal and basal invasive ductal carcinomas. Here we show that E-cadherin promotes metastasis in diverse models of invasive ductal carcinomas. While loss of E-cadherin increased invasion, it also reduced cancer cell proliferation and survival, circulating tumour cell number, seeding of cancer cells in distant organs and metastasis outgrowth. Transcriptionally, loss of E-cadherin was associated with upregulation of genes involved in transforming growth factor-ß (TGFß), reactive oxygen species and apoptosis signalling pathways. At the cellular level, disseminating E-cadherin-negative cells exhibited nuclear enrichment of SMAD2/3, oxidative stress and increased apoptosis. Colony formation of E-cadherin-negative cells was rescued by inhibition of TGFß-receptor signalling, reactive oxygen accumulation or apoptosis. Our results reveal that E-cadherin acts as a survival factor in invasive ductal carcinomas during the detachment, systemic dissemination and seeding phases of metastasis by limiting reactive oxygen-mediated apoptosis. Identifying molecular strategies to inhibit E-cadherin-mediated survival in metastatic breast cancer cells may have potential as a therapeutic approach for breast cancer.

Priors, population sizes, and power in genome-wide hypothesis tests.

BACKGROUND: Genome-wide tests, including genome-wide association studies (GWAS) of germ-line genetic variants, driver tests of cancer somatic mutations, and transcriptome-wide association tests of RNAseq data, carry a high multiple testing burden. This burden can be overcome by enrolling larger cohorts or alleviated by using prior biological knowledge to favor some hypotheses over others. Here we compare these two methods in terms of their abilities to boost the power of hypothesis testing. RESULTS: We provide a quantitative estimate for progress in cohort sizes and present a theoretical analysis of the power of oracular hard priors: priors that select a subset of hypotheses for testing, with an oracular guarantee that all true positives are within the tested subset. This theory demonstrates that for GWAS, strong priors that limit testing to 100-1000 genes provide less power than typical annual 20-40% increases in cohort sizes. Furthermore, non-oracular priors that exclude even a small fraction of true positives from the tested set can perform worse than not using a prior at all. CONCLUSION: Our results provide a theoretical explanation for the continued dominance of simple, unbiased univariate hypothesis tests for GWAS: if a statistical question can be answered by larger cohort sizes, it should be answered by larger cohort sizes rather than by more complicated biased methods involving priors. We suggest that priors are better suited for non-statistical aspects of biology, such as pathway structure and causality, that are not yet easily captured by standard hypothesis tests.

Probing nucleosome function: a highly versatile library of synthetic histone H3 and H4 mutants.

Nucleosome structural integrity underlies the regulation of DNA metabolism and transcription. Using a synthetic approach, a versatile library of 486 systematic histone H3 and H4 substitution and deletion mutants that probes the contribution of each residue to nucleosome function was generated in Saccharomyces cerevisiae. We probed fitness contributions of each residue to perturbations of chromosome integrity and transcription, mapping global patterns of chemical sensitivities and requirements for transcriptional silencing onto the nucleosome surface. Each histone mutant was tagged with unique molecular barcodes, facilitating identification of histone mutant pools through barcode amplification, labeling, and TAG microarray hybridization. Barcodes were used to score complex phenotypes such as competitive fitness in a chemostat, DNA repair proficiency, and synthetic genetic interactions, revealing new functions for distinct histone residues and new interdependencies among nucleosome components and their modifiers.

Myocardial Gene Expression Signatures in Human Heart Failure With Preserved Ejection Fraction.

BACKGROUND: Heart failure (HF) with preserved ejection fraction (HFpEF) constitutes half of all HF but lacks effective therapy. Understanding of its myocardial biology remains limited because of a paucity of heart tissue molecular analysis. METHODS: We performed RNA sequencing on right ventricular septal endomyocardial biopsies prospectively obtained from patients meeting consensus criteria for HFpEF (n=41) contrasted with right ventricular septal tissue from patients with HF with reduced ejection fraction (HFrEF, n=30) and donor controls (n=24). Principal component analysis and hierarchical clustering tested for transcriptomic distinctiveness between groups, effect of comorbidities, and differential gene expression with pathway enrichment contrasted HF groups and donor controls. Within HFpEF, non-negative matrix factorization and weighted gene coexpression analysis identified molecular subgroups, and the resulting clusters were correlated with hemodynamic and clinical data. RESULTS: Patients with HFpEF were more often women (59%), African American (68%), obese (median body mass index 41), and hypertensive (98%), with clinical HF characterized by 65% New York Heart Association Class III or IV, nearly all on a loop diuretic, and 70% with a HF hospitalization in the previous year. Principal component analysis separated HFpEF from HFrEF and donor controls with minimal overlap, and this persisted after adjusting for primary comorbidities: body mass index, sex, age, diabetes, and renal function. Hierarchical clustering confirmed group separation. Nearly half the significantly altered genes in HFpEF versus donor controls (1882 up, 2593 down) changed in the same direction in HFrEF; however, 5745 genes were uniquely altered between HF groups. Compared with controls, uniquely upregulated genes in HFpEF were enriched in mitochondrial adenosine triphosphate synthesis/electron transport, pathways downregulated in HFrEF. HFpEF-specific downregulated genes engaged endoplasmic reticulum stress, autophagy, and angiogenesis. Body mass index differences largely accounted for HFpEF upregulated genes, whereas neither this nor broader comorbidity adjustment altered pathways enriched in downregulated genes. Non-negative matrix factorization identified 3 HFpEF transcriptomic subgroups with distinctive pathways and clinical correlates, including a group closest to HFrEF with higher mortality, and a mostly female group with smaller hearts and proinflammatory signaling. These groupings remained after sex adjustment. Weighted gene coexpression analysis yielded analogous gene clusters and clinical groupings. CONCLUSIONS: HFpEF exhibits distinctive broad transcriptomic signatures and molecular subgroupings with particular clinical features and outcomes. The data reveal new signaling targets to consider for precision therapeutics.

OrgDyn: feature- and model-based characterization of spatial and temporal organoid dynamics.

SUMMARY: Organoid model systems recapitulate key features of mammalian tissues and enable high throughput experiments. However, the impact of these experiments may be limited by manual, non-standardized, static or qualitative phenotypic analysis. OrgDyn is an open-source and modular pipeline to quantify organoid shape dynamics using a combination of feature- and model-based approaches on time series of 2D organoid contour images. Our pipeline consists of (i) geometrical and signal processing feature extraction, (ii) dimensionality reduction to differentiate dynamical paths, (iii) time series clustering to identify coherent groups of organoids and (iv) dynamical modeling using point distribution models to explain temporal shape variation. OrgDyn can characterize, cluster and model differences among unique dynamical paths that define diverse final shapes, thus enabling quantitative analysis of the molecular basis of tissue development and disease. AVAILABILITY AND IMPLEMENTATION: https://github.com/zakih/organoidDynamics (BSD 3-Clause License). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Between-tumor and within-tumor heterogeneity in invasive potential.

For women with access to healthcare and early detection, breast cancer deaths are caused primarily by metastasis rather than growth of the primary tumor. Metastasis has been difficult to study because it happens deep in the body, occurs over years, and involves a small fraction of cells from the primary tumor. Furthermore, within-tumor heterogeneity relevant to metastasis can also lead to therapy failures and is obscured by studies of bulk tissue. Here we exploit heterogeneity to identify molecular mechanisms of metastasis. We use "organoids", groups of hundreds of tumor cells taken from a patient and grown in the lab, to probe tumor heterogeneity, with potentially thousands of organoids generated from a single tumor. We show that organoids have the character of biological replicates: within-tumor and between-tumor variation are of similar magnitude. We develop new methods based on population genetics and variance components models to build between-tumor and within-tumor statistical tests, using organoids analogously to large sibships and vastly amplifying the test power. We show great efficiency for tests based on the organoids with the most extreme phenotypes and potential cost savings from pooled tests of the extreme tails, with organoids generated from hundreds of tumors having power predicted to be similar to bulk tests of hundreds of thousands of tumors. We apply these methods to an association test for molecular correlates of invasion, using a novel quantitative invasion phenotype calculated as the spectral power of the organoid boundary. These new approaches combine to show a strong association between invasion and protein expression of Keratin 14, a known biomarker for poor prognosis, with p = 2 × 10-45 for within-tumor tests of individual organoids and p < 10-6 for pooled tests of extreme tails. Future studies using these methods could lead to discoveries of new classes of cancer targets and development of corresponding therapeutics. All data and methods are available under an open source license at https://github.com/baderzone/invasion_2019.

Schizophrenia risk alleles often affect the expression of many genes and each gene may have a different effect on the risk: A mediation analysis.

Variants identified by genome-wide association studies (GWAS) are often expression quantitative trait loci (eQTLs), suggesting they are proxies or are themselves regulatory. Across many data sets, analyses show that variants often affect multiple genes. Lacking data on many tissue types, developmental time points, and homogeneous cell types, the extent of this one-to-many relationship is underestimated. This raises questions on whether a disease eQTL target gene explains the genetic association or is a bystander and puts into question the direction of expression effect of on the risk, since the many variants-regulated genes may have opposing effects, imperfectly balancing each other. We used two brain gene expression data sets (CommonMind and BrainSeq) for mediation analysis of schizophrenia-associated variants. We confirm that eQTL target genes often mediate risk but the direction in which expression affects risk is often different from that in which the risk allele changes expression. Of 38 mediator genes significant in both data sets 33 showed consistent mediation direction (Chi2 test p = 6 × 10-6 ). One might expect that the expression would correlate with the risk allele in the same direction it correlates with the disease. For 15 of these 33 (45%), however, the expression change associated with the risk allele was protective, suggesting the likely presence of other target genes with overriding effects. Our results identify specific risk mediating genes and suggest caution in interpreting the biological consequences of targeted modifications of gene expression, as not all eQTL targets may be relevant to disease while those that are, might have different from expected directions.

Low escape-rate genome safeguards with minimal molecular perturbation of Saccharomyces cerevisiae.

As the use of synthetic biology both in industry and in academia grows, there is an increasing need to ensure biocontainment. There is growing interest in engineering bacterial- and yeast-based safeguard (SG) strains. First-generation SGs were based on metabolic auxotrophy; however, the risk of cross-feeding and the cost of growth-controlling nutrients led researchers to look for other avenues. Recent strategies include bacteria engineered to be dependent on nonnatural amino acids and yeast SG strains that have both transcriptional- and recombinational-based biocontainment. We describe improving yeast Saccharomyces cerevisiae-based transcriptional SG strains, which have near-WT fitness, the lowest possible escape rate, and nanomolar ligands controlling growth. We screened a library of essential genes, as well as the best-performing promoter and terminators, yielding the best SG strains in yeast. The best constructs were fine-tuned, resulting in two tightly controlled inducible systems. In addition, for potential use in the prevention of industrial espionage, we screened an array of possible "decoy molecules" that can be used to mask any proprietary supplement to the SG strain, with minimal effect on strain fitness.

SCRaMbLE generates designed combinatorial stochastic diversity in synthetic chromosomes.

Synthetic chromosome rearrangement and modification by loxP-mediated evolution (SCRaMbLE) generates combinatorial genomic diversity through rearrangements at designed recombinase sites. We applied SCRaMbLE to yeast synthetic chromosome arm synIXR (43 recombinase sites) and then used a computational pipeline to infer or unscramble the sequence of recombinations that created the observed genomes. Deep sequencing of 64 synIXR SCRaMbLE strains revealed 156 deletions, 89 inversions, 94 duplications, and 55 additional complex rearrangements; several duplications are consistent with a double rolling circle mechanism. Every SCRaMbLE strain was unique, validating the capability of SCRaMbLE to explore a diverse space of genomes. Rearrangements occurred exclusively at designed loxPsym sites, with no significant evidence for ectopic rearrangements or mutations involving synthetic regions, the 99% nonsynthetic nuclear genome, or the mitochondrial genome. Deletion frequencies identified genes required for viability or fast growth. Replacement of 3' UTR by non-UTR sequence had surprisingly little effect on fitness. SCRaMbLE generates genome diversity in designated regions, reveals fitness constraints, and should scale to simultaneous evolution of multiple synthetic chromosomes.

Polyclonal breast cancer metastases arise from collective dissemination of keratin 14-expressing tumor cell clusters.

Recent genomic studies challenge the conventional model that each metastasis must arise from a single tumor cell and instead reveal that metastases can be composed of multiple genetically distinct clones. These intriguing observations raise the question: How do polyclonal metastases emerge from the primary tumor? In this study, we used multicolor lineage tracing to demonstrate that polyclonal seeding by cell clusters is a frequent mechanism in a common mouse model of breast cancer, accounting for >90% of metastases. We directly observed multicolored tumor cell clusters across major stages of metastasis, including collective invasion, local dissemination, intravascular emboli, circulating tumor cell clusters, and micrometastases. Experimentally aggregating tumor cells into clusters induced a >15-fold increase in colony formation ex vivo and a >100-fold increase in metastasis formation in vivo. Intriguingly, locally disseminated clusters, circulating tumor cell clusters, and lung micrometastases frequently expressed the epithelial cytoskeletal protein, keratin 14 (K14). RNA-seq analysis revealed that K14(+) cells were enriched for desmosome and hemidesmosome adhesion complex genes, and were depleted for MHC class II genes. Depletion of K14 expression abrogated distant metastases and disrupted expression of multiple metastasis effectors, including Tenascin C (Tnc), Jagged1 (Jag1), and Epiregulin (Ereg). Taken together, our findings reveal K14 as a key regulator of metastasis and establish the concept that K14(+) epithelial tumor cell clusters disseminate collectively to colonize distant organs.

Tissue matrix arrays for high-throughput screening and systems analysis of cell function.

Cell and protein arrays have demonstrated remarkable utility in the high-throughput evaluation of biological responses; however, they lack the complexity of native tissue and organs. Here we spotted tissue extracellular matrix (ECM) particles as two-dimensional (2D) arrays or incorporated them with cells to generate three-dimensional (3D) cell-matrix microtissue arrays. We then investigated the responses of human stem, cancer and immune cells to tissue ECM arrays originating from 11 different tissues. We validated the 2D and 3D arrays as representative of the in vivo microenvironment by means of quantitative analysis of tissue-specific cellular responses, including matrix production, adhesion and proliferation, and morphological changes after culture. The biological outputs correlated with tissue proteomics, and network analysis identified several proteins linked to cell function. Our methodology enables broad screening of ECMs to connect tissue-specific composition with biological activity, providing a new resource for biomaterials research and further understanding of regeneration and disease mechanisms.

Functional dissection of lysine deacetylases reveals that HDAC1 and p300 regulate AMPK.

First identified as histone-modifying proteins, lysine acetyltransferases (KATs) and deacetylases (KDACs) antagonize each other through modification of the side chains of lysine residues in histone proteins. Acetylation of many non-histone proteins involved in chromatin, metabolism or cytoskeleton regulation were further identified in eukaryotic organisms, but the corresponding enzymes and substrate-specific functions of the modifications are unclear. Moreover, mechanisms underlying functional specificity of individual KDACs remain enigmatic, and the substrate spectra of each KDAC lack comprehensive definition. Here we dissect the functional specificity of 12 critical human KDACs using a genome-wide synthetic lethality screen in cultured human cells. The genetic interaction profiles revealed enzyme-substrate relationships between individual KDACs and many important substrates governing a wide array of biological processes including metabolism, development and cell cycle progression. We further confirmed that acetylation and deacetylation of the catalytic subunit of the adenosine monophosphate-activated protein kinase (AMPK), a critical cellular energy-sensing protein kinase complex, is controlled by the opposing catalytic activities of HDAC1 and p300. Deacetylation of AMPK enhances physical interaction with the upstream kinase LKB1, leading to AMPK phosphorylation and activation, and resulting in lipid breakdown in human liver cells. These findings provide new insights into previously underappreciated metabolic regulatory roles of HDAC1 in coordinating nutrient availability and cellular responses upstream of AMPK, and demonstrate the importance of high-throughput genetic interaction profiling to elucidate functional specificity and critical substrates of individual human KDACs potentially valuable for therapeutic applications.

Intrinsic biocontainment: multiplex genome safeguards combine transcriptional and recombinational control of essential yeast genes.

Biocontainment may be required in a wide variety of situations such as work with pathogens, field release applications of engineered organisms, and protection of intellectual properties. Here, we describe the control of growth of the brewer's yeast, Saccharomyces cerevisiae, using both transcriptional and recombinational "safeguard" control of essential gene function. Practical biocontainment strategies dependent on the presence of small molecules require them to be active at very low concentrations, rendering them inexpensive and difficult to detect. Histone genes were controlled by an inducible promoter and controlled by 30 nM estradiol. The stability of the engineered genes was separately regulated by the expression of a site-specific recombinase. The combined frequency of generating viable derivatives when both systems were active was below detection (<10(-10)), consistent with their orthogonal nature and the individual escape frequencies of <10(-6). Evaluation of escaper mutants suggests strategies for reducing their emergence. Transcript profiling and growth test suggest high fitness of safeguarded strains, an important characteristic for wide acceptance.

Hypoxia Sensing and Persistence Genes Are Expressed during the Intragranulomatous Survival of Mycobacterium tuberculosis.

Although it is accepted that the environment within the granuloma profoundly affects Mycobacterium tuberculosis (Mtb) and infection outcome, our ability to understand Mtb gene expression in these niches has been limited. We determined intragranulomatous gene expression in human-like lung lesions derived from nonhuman primates with both active tuberculosis (ATB) and latent TB infection (LTBI). We employed a non-laser-based approach to microdissect individual lung lesions and interrogate the global transcriptome of Mtb within granulomas. Mtb genes expressed in classical granulomas with central, caseous necrosis, as well as within the caseum itself, were identified and compared with other Mtb lesions in animals with ATB (n = 7) or LTBI (n = 7). Results were validated using both an oligonucleotide approach and RT-PCR on macaque samples and by using human TB samples. We detected approximately 2,900 and 1,850 statistically significant genes in ATB and LTBI lesions, respectively (linear models for microarray analysis, Bonferroni corrected, P < 0.05). Of these genes, the expression of approximately 1,300 (ATB) and 900 (LTBI) was positively induced. We identified the induction of key regulons and compared our results to genes previously determined to be required for Mtb growth. Our results indicate pathways that Mtb uses to ensure its survival in a highly stressful environment in vivo. A large number of genes is commonly expressed in granulomas with ATB and LTBI. In addition, the enhanced expression of the dormancy survival regulon was a key feature of lesions in animals with LTBI, stressing its importance in the persistence of Mtb during the chronic phase of infection.