Structural genomics seeks to expand rapidly the number of protein structures in order to extract the maximum amount of information from genomic sequence databases. The advent of several large-scale projects worldwide leads to many new challenges in the ®eld of crystallographic macromolecular structure determination. A novel software package called PHENIX (Python-based Hierarchical ENvironment for Integrated Xtallography) is therefore being developed. This new software will provide the necessary algorithms to proceed from reduced intensity data to a re®ned molecular model and to facilitate structure solution for both the novice and expert crystallographer.

The pathways that comprise cellular metabolism are highly interconnected, and alterations in individual enzymes can have far-reaching effects. As a result, global profiling methods that measure gene expression are of limited value in predicting how the loss of an individual function will affect the cell. In this work, we employed a new method of global phenotypic profiling to directly define the genes required for the growth of Mycobacterium tuberculosis. A combination of high-density mutagenesis and deep-sequencing was used to characterize the composition of complex mutant libraries exposed to different conditions. This allowed the unambiguous identification of the genes that are essential for Mtb to grow in vitro, and proved to be a significant improvement over previous approaches. To further explore functions that are required for persistence in the host, we defined the pathways necessary for the utilization of cholesterol, a critical carbon source during infection. Few of the genes we identified had previously been implicated in this adaptation by transcriptional profiling, and only a fraction were encoded in the chromosomal region known to encode sterol catabolic functions. These genes comprise an unexpectedly large percentage of those previously shown to be required for bacterial growth in mouse tissue. Thus, this single nutritional change accounts for a significant fraction of the adaption to the host. This work provides the most comprehensive genetic characterization of a sterol catabolic pathway to date, suggests putative roles for uncharacterized virulence genes, and precisely maps genes encoding potential drug targets.

For decades, identifying the regions of a bacterial chromosome that are necessary for viability has relied on mapping integration sites in libraries of random transposon mutants to find loci that are unable to sustain insertion. To date, these studies have analyzed subsaturated libraries, necessitating the application of statistical methods to estimate the likelihood that a gap in transposon coverage is the result of biological selection and not the stochasticity of insertion. As a result, the essentiality of many genomic features, particularly small ones, could not be reliably assessed. We sought to overcome this limitation by creating a completely saturated transposon library in Mycobacterium tuberculosis. In assessing the composition of this highly saturated library by deep sequencing, we discovered that a previously unknown sequence bias of the Himar1 element rendered approximately 9% of potential TA dinucleotide insertion sites less permissible for insertion. We used a hidden Markov model of essentiality that accounted for this unanticipated bias, allowing us to confidently evaluate the essentiality of features that contained as few as 2 TA sites, including open reading frames (ORF), experimentally identified noncoding RNAs, methylation sites, and promoters. In addition, several essential regions that did not correspond to known features were identified, suggesting uncharacterized functions that are necessary for growth. This work provides an authoritative catalog of essential regions of the M. tuberculosis genome and a statistical framework for applying saturating mutagenesis to other bacteria.

Over 30% of the world’s population is infected with Mycobacterium tuberculosis (Mtb), yet only ~5–10% will develop clinical disease1. Despite considerable effort, we understand little about what distinguishes individuals who progress to active tuberculosis (TB) from those who remain latent for decades. The variable course of disease is recapitulated in cynomolgus macaques infected with Mtb2. Active disease in macaques is defined by clinical, microbiologic and immunologic signs and occurs in ~45% of animals, while the remaining are clinically asymptomatic2,3. Here, we use barcoded Mtb isolates and quantitative measures of culturable and cumulative bacterial burden to show that most lesions are likely founded by a single bacterium and reach similar maximum burdens. Despite common origins, the fate of individual lesions varies substantially within the same host. Strikingly, in active disease, the host sterilizes some lesions even while others progress. Our data suggest that lesional heterogeneity arises, in part, through differential killing of bacteria after the onset of adaptive immunity. Thus, individual lesions follow diverse and overlapping trajectories, suggesting critical responses occur at a lesional level to ultimately determine the clinical outcome of infection. Defining the local factors that dictate outcome will be important in developing effective interventions to prevent active TB.

Running title: Automated structure solution with PHENIX Abstract Significant time and effort are often required to solve and complete a macromolecular crystal structure.The development of automated computational methods for the analysis, solution and completion of crystallographic structures has the potential to produce minimally biased models in a short time without the need for manual intervention. The PHENIX software suite is a highly 2 automated system for macromolecular structure determination that can rapidly arrive at an initial partial model of a structure without significant human intervention, given moderate resolution and good quality data. This achievement has been made possible by the development of new algorithms for structure determination, maximum-likelihood molecular replacement (PHASER), heavy-atom search (HySS), template and pattern-based automated model-building (RESOLVE, TEXTAL), automated macromolecular refinement (phenix.refine), and iterative model-building, density modification and refinement that can operate at moderate resolution (RESOLVE, AutoBuild). These algorithms are based on a highly integrated and comprehensive set of crystallographic libraries that have been built and made available to the community. The algorithms are tightly linked and made easily accessible to users through the PHENIX Wizards and the PHENIX GUI.

Summary Bacteria that cause disease rely on their ability to counteract and overcome host defenses. Here we present a genome-scale study of Mycobacterium tuberculosis (Mtb) that uncovers the bacterial determinants of surviving host immunity, sets of genes we term “counteractomes.” Through this, we find that CD4 T cells attempt to starve Mtb of tryptophan through a mechanism that limits Chlamydia and Leishmania infections. In those cases, tryptophan starvation works well, since those pathogens are natural tryptophan auxotrophs. Mtb, however, can synthesize tryptophan, and thus starvation fails as an Mtb-killing mechanism. We then describe a small molecule inhibitor of Mtb tryptophan synthesis, which turns Mtb into a tryptophan auxotroph and restores the efficacy of a failed host defense. Together, our findings demonstrate that the Mtb determinants for surviving host immunity—Mtb’s immune counteractomes—serve as probes of host immunity, uncovering immune-mediated stresses that can be leveraged for therapeutic discovery.

Mycobacterium tuberculosis (Mtb) has generated a global health catastrophe that has been compounded by the emergence of drug resistant Mtb strains. We used whole genome sequencing to compare the accumulation of mutations in Mtb isolated from cynomolgus macaques with active, latent and reactivated disease. Based on the distribution of SNPs observed, we calculated the mutation rates for these disease states. Our data suggest that Mtb acquires a similar number of chromosomal mutations during latency as occurs during active disease or in a logarithmically growing culture over the same period of time despite reduced bacterial replication during latent infection. The pattern of polymorphisms suggests that the mutational burden in vivo is due to oxidative DNA damage. Thus, we demonstrate that Mtb continues to acquire mutations during latency and provide a novel explanation for the observation that isoniazid monotherapy for latent tuberculosis is a risk factor for the emergence of INH resistance1,2.

RNA-seq technologies have provided significant insight into the transcription networks of mycobacteria. However, such studies provide no definitive information on the translational landscape. Here, we use a combination of high-throughput transcriptome and proteome-profiling approaches to more rigorously understand protein expression in two mycobacterial species. RNA-seq and ribosome profiling in Mycobacterium smegmatis, and transcription start site (TSS) mapping and N-terminal peptide mass spectrometry in Mycobacterium tuberculosis, provide complementary, empirical datasets to examine the congruence of transcription and translation in the Mycobacterium genus. We find that nearly one-quarter of mycobacterial transcripts are leaderless, lacking a 5’ untranslated region (UTR) and Shine-Dalgarno ribosome-binding site. Our data indicate that leaderless translation is a major feature of mycobacterial genomes and is comparably robust to leadered initiation. Using translational reporters to systematically probe the cis-sequence requirements of leaderless translation initiation in mycobacteria, we find that an ATG or GTG at the mRNA 5’ end is both necessary and sufficient. This criterion, together with our ribosome occupancy data, suggests that mycobacteria encode hundreds of small, unannotated proteins at the 5’ ends of transcripts. The conservation of small proteins in both mycobacterial species tested suggests that some play important roles in mycobacterial physiology. Our translational-reporter system further indicates that mycobacterial leadered translation initiation requires a Shine Dalgarno site in the 5’ UTR and that ATG, GTG, TTG, and ATT codons can robustly initiate translation. Our combined approaches provide the first comprehensive view of mycobacterial gene structures and their non-canonical mechanisms of protein expression.