The genome sequencing of H37Rv strain of Mycobacterium tuberculosis was completed in 1998 followed by the whole genome sequencing of a clinical isolate, CDC1551 in 2002. Since then, the genomic sequences of a number of other strains have become available making it one of the better studied pathogenic bacterial species at the genomic level. However, annotation of its genome remains challenging because of high GC content and dissimilarity to other model prokaryotes. To this end, we carried out an in-depth proteogenomic analysis of the M. tuberculosis H37Rv strain using Fourier transform mass spectrometry with high resolution at both MS and tandem MS levels. In all, we identified 3176 proteins from Mycobacterium tuberculosis representing ϳ80% of its total predicted gene count. In addition to protein database search, we carried out a genome database search, which led to identification of ϳ250 novel peptides. Based on these novel genome search-specific peptides, we discovered 41 novel protein coding genes in the H37Rv genome. Using peptide evidence and alternative gene prediction tools, we also corrected 79 gene models. Finally, mass spectrometric data from N terminus-derived peptides confirmed 727 existing annotations for translational start sites while correcting those for 33 proteins. We report creation of a high confidence set of protein coding regions in Mycobacterium tuberculosis genome obtained by high resolution tandem mass-spectrometry at both precursor and fragment detection steps for the first time. This proteogenomic approach should be generally applicable to other organisms whose genomes have already been sequenced for obtaining a more accurate catalogue of protein-coding genes.

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The tubercle complex consists of closely related mycobacterium species which appear to be variants of a single species. Comparative genome analysis of different strains could provide useful clues and insights into the genetic diversity of the species. We integrated genome assemblies of 96 strains from Mycobacterium tuberculosis complex (MTBC), which included 8 Indian clinical isolates sequenced and assembled in this study, to understand its pangenome architecture. We predicted genes for all the 96 strains and clustered their respective CDSs into homologous gene clusters (HGCs) to reveal a hard-core, soft-core and accessory genome component of MTBC. The hard-core (HGCs shared amongst 100% of the strains) was comprised of 2,066 gene clusters whereas the soft-core (HGCs shared amongst at least 95% of the strains) comprised of 3,374 gene clusters. The change in the core and accessory genome components when observed as a function of their size revealed that MTBC has an open pangenome. We identified 74 HGCs that were absent from reference strains H37Rv and H37Ra but were present in most of clinical isolates. We report PCR validation on 9 candidate genes depicting 7 genes completely absent from H37Rv and H37Ra whereas 2 genes shared partial homology with them accounting to probable insertion and deletion events. The pangenome approach is a promising tool for studying strain specific genetic differences occurring within species. We also suggest that since selecting appropriate target genes for typing purposes requires the expected target gene be present in all isolates being typed, therefore estimating the core-component of the species becomes a subject of prime importance.

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This paper describes the design and implementation of the Mobile Objects and Agents (MOA) project at the Open Group Research Institute. MOA was designed to support migration, communication and control of agents. It was implemented on top of the Java Virtual Machine, without any modifications to it. The initial project goals were to support communication across agent migration, as a means for collaborative work; and to provide extensive resource control, as a basic support for countering denial of service attacks. In the course of the project we added two further goals: compliance with the Java Beans component model which provides for additional configurability and customization of agent system and agent applications; and interoperability which allows cooperation with other agent systems.This paper analyzes the architecture of MOA, in particular the support for mobility, naming and locating, communication, and resource management. Object and component models of MOA are discussed and some implementation details described. We summarize the lessons learned while developing and implementing MOA and compare it to related work. IntroductionMobility has always attracted researchers in computer science. This interest spans from general observations, such as "if it weren't for mobility, we would still be trees" [10], and the analogies with the real world "migrating birds and nomadic tribes moving due to the lack of resources", to purely technical reasons, such as improving locality of reference and difference between local and remote semantics.One of the first incarnations of software mobile entities. is worms [30], which could spread across nodes and arbitrarily clone. Unrestricted implementations of worms and viruses have received negative connotations, due to security breaches and denial of service attacks [13].The next generation of mobile entities, known as process migration, were implemented at the operating sysThis work was supported in part by the Advanced Research Projects Agency and the Rome Laboratory of the Air Force Materiel Command. tem (OS) level. There were many implementations of process and object migration [3,12,19,31], but none has achieved wide acceptance. Due to inherent complexity, it was hard to introduce process migration without impacting the stability and robustness of the underlying OS.Mobile objects and agents have attracted significant attention recently. In addition to mobile code (such as applets), agents consist of data and non-transient system state that can travel between the nodes in a distributed system (intranet or Internet). Compared to mobile objects, mobile agents also represent someone; they can perform autonomous actions on behalf of a user or another agent. This paper describes the Mobile Objects and Agents (MOA) project at the Open Group Research Institute. The obvious question is why yet another mobile agent system? There were a few reasons. None of the existing systems at the time of starting the project were mature enough to be used as a starting point for our wor...