Proteins orchestrate a number of cellular processes either alone or in concert with other biomolecules like nucleic acids, carbohydrates, and lipids. They exhibit an intrinsic ability to fold de novo to their functional states. The three–dimensional structure of a protein, dependent on its amino acid sequence, is important for its function. Understanding this sequence– structure–function relationship has become one of the primary goals in biophysics. Various experimental techniques like X–ray crystallography, Nuclear Magnetic Resonance (NMR), and site–directed mutagenesis have been used extensively towards this goal. Computational studies include mainly sequence based, and structure based approaches. The sequence based approaches such as sequence alignments, phylogenetic analysis, domain identification, statistical coupling analysis etc., aim at deriving meaningful information from the primary sequence of the protein. The structure based approaches, on the other hand, use structures of folded proteins. Recent advances in structure determination and efforts by various structural consortia have resulted in an enormous amount of structures available for analysis. Innumerable observations such as the allowed and disallowed regions in the conformations of a peptide unit, hydrophobic core in globular proteins, existence of regular secondary structures like helices, sheets, and turns and a limited fold space have been landmarks in understanding the characteristics of protein structures. The uniqueness of protein structure is attained through non–covalent interactions among the constituent amino acids. Analyses of protein structures show that different types of non–covalent interactions like hydrophobic interactions, hydrogen bonding, salt bridges, aromatic stacking, cation–π interactions, and solvent interactions hold protein structures together. Although such structure analyses have provided a wealth of information, they have largely been performed at a pair–wise level and an investigation involving such pair–wise interactions alone is not sufficient to capture all the determinants of protein structures, since they happen at a global level. This consideration has led to the development of graphs/networks for proteins. Graphs or Networks are a collection of nodes connected by edges. Protein Structure Networks (PSNs) can be constructed using various definitions of nodes and edges. Nodes may vary from atoms to secondary structures in Synopsis proteins, and the edges can range from simple atom–atom distances to distance between secondary structures. To study the interplay of amino acids in structure formation, the most commonly used PSNs consider amino acids as nodes. The criterion for edge definition, however, varies. PSNs can be constructed at a course grain level by considering the distances between Cα/Cβ atoms, any side–chain atoms, or the centroids of the amino acids. At a finer level, PSNs can be constructed using atomic details by considering the interaction types or by computing the extent of interaction between amino acids. Representation of proteins as networks and their analyses has given us a unique perspective on various aspects such as protein structure organization, stability, folding, function, oligomerization and so on. A variety of network properties like the degree distribution, clustering coefficient, characteristic path lengths, clusters, and hubs have been investigated. Most of these studies are carried out on protein structures alone. However, the interaction of proteins with other biopolymers like nucleic acids is vital for many crucial biological processes like transcription and translation. In this thesis, we have attempted to address this problem by constructing and analyzing combined graphs of the structures of protein and DNA. Also, in almost all of the PSN studies, the connections have been made solely on the basis of geometric criteria. In the later part of the thesis, we have taken PSN a step further by defining the non–covalent connections based on chemical considerations in the form of the energies of interactions. The thesis contains two sections. The first part mainly involves the construction and application of PSNs to study DNA binding proteins. The DNA binding proteins are involved in several high fidelity processes like DNA recombination, DNA replication, and transcription. Although the protein– DNA interfaces have been extensively analyzed using pair–wise interactions, we gain additional global perspective from network approach. Furthermore, most of the earlier investigations have been carried out from the protein point of view (protein centric) and the present network approach aims to combine both the protein centric and the DNA centric view points by construction and analyses of protein–DNA graphs. These studies are described in Chapters 3 and 4. The second part of the thesis discusses the development, characterization, and application of protein structure networks based on non– covalent interaction energies. The investigations are presented in chapters 5 and 6. Chapter 3 discusses the development of Protein–DNA Graphs (PDGs) where the protein–DNA interfaces are represented as networks. PDG is a bipartite network in which amino acids form a set of nodes and the nucleotides form the other set. The extent of interaction between the two diverse types of biopolymers is normalized to define the strength of interaction. Edges are then constructed based on the interaction strength between amino acids and nucleotides. Such a representation, reported here for the first time, provides a holistic view of the interacting surface. The developed PDGs are further analyzed in terms of clusters of interacting residues and identification of highly connected residues, known as hubs, along the protein–DNA interface and discussed in terms of their interacting motifs. Important clusters have been identified in a set of protein–DNA complexes, where the amino acids interact with different chemical components of DNA such as phosphate, deoxyribose and base with varying degrees of connectivity. An analysis of such fragment based PDGs provided insights into the nature of protein–DNA interaction, which could not have been obtained by conventional pair–wise analysis. The predominance of deoxyribose–amino acid clusters in beta–sheet proteins, distinction of the interface clusters in helix–turn–helix and the zipper type proteins are some of the new findings from the analysis of PDGs. Additionally, a potential classification scheme has been proposed for protein–DNA complexes on the basis of their interface clusters. This classification scheme gives a general idea of how the proteins interact with different components of DNA in various complexes. The present graph–based method has provided a deeper insight into the analysis of the protein–DNA recognition mechanisms from both protein and DNA view points, thus throwing more light on the nature and specificity of these interactions (Sathyapriya, Vijayabaskar et al. 2008). Chapter 4 delineates the application of PSN to an important problem in molecular biology. An analysis of interface clusters from multimeric proteins provides a clue to the important residues contributing to the stability of the oligomers. One such prediction was made on the DNA binding protein under starvation from Mycobacterium smegmatis (Ms–Dps) using PSNs. Two types of trimers, Trimer A (tA) and Trimer B (tB) can be derived from the dodecamer because of the inherent three fold symmetry of the spherical crystal structure. The irreversible dodecamerization of these native Ms--Dps trimers, in vitro, is known to be directly associated with the bimodal function (DNA binding and iron storage) of this protein. Interface clusters which were Synopsis identified from the PSNs of the derived trimers, allowed us to convincingly predict the residues E146 and F47 for mutation studies. The prediction was followed up by our experimental collaborators (Rakhi PC and Dipankar Chatterji), which led to the elucidation of the molecular mechanism behind the in vitro oligomerization of Ms--Dps. The F47E mutant was impaired in dodecamerization, and the double mutant (E146AF47E) was a native monomer in solution. These two observations suggested that the two trimers are important for dodecamerization and that the residues selected are important for the structural stability of the protein in vitro. From the structural and functional characterizations of the mutants, we have proposed an oligomerization pathway of Ms–Dps (Chowdhury, Vijayabaskar et al. 2008). The second part of the thesis involves the development, characterization (Chapter 5) and application (Chapter 6) of Protein Energy Networks (PENs). As mentioned above, the PSNs constructed on the geometric basis efficiently capture the topology and associated properties at the level of atom–atom contact. The chemistry, however, is not completely captured by these network representations, and a wealth of information can be extracted by incorporating the details of chemical interactions. This study is an advancement over the existing PSNs, in terms of edges being defined on the basis of interaction energies among the amino acids. This interaction energy is the resultant of various types of interactions within a protein. Use of such realistic interaction energies in a weighted network captures all the essential features responsible for maintaining the protein structure. The methodology involved in representing proteins as interaction energy weighted networks, with realistic edge weights obtained from standard force fields is described in Chapter 5. The interaction energies were derived from equilibrium ensembles (obtained using molecular dynamics simulations) to account for the structural plasticity, which is essential for function elucidation. The suitability of this method to study single static structures was validated by obtaining interaction energies on minimized crystal structures of proteins. The PENs were then characterized using network parameters like edge weight distributions, clusters, hubs, and shortest paths. The PENs exhibited three distinct behaviors in terms of the size of the largest connected cluster as a function of interaction energy; namely, the pre–transition, transition, and post transition regions, irrespective of the topology of the proteins. The pre– transition region (energies<–20 kJ/mol) comprises smaller clusters with mainly charged and polar residues as hubs. Crucial topological changes take place in the transition region (–10 to –20 kJ/mol), where the smaller clusters aggregate, through low energy van der Waals interactions, to form a single large cluster in the post–transition region (energies>–10 kJ/mol). These behaviors reinforce the concept that hydrophobic interactions hold together local clusters of highly interacting residues, keeping the protein topology intact (Vijayabaskar and Vishveshwara 2010). The applications of PENs in studying protein organization, allosteric communication, thermophilic stability and the structural relation of remote homologues of TIM barrel families have been outlined in Chapter 6. In the first case, the weighted networks were used to identify stabilization regions in protein structures and hierarchical organization in the folded proteins, which may provide some insights into the general mechanism of protein folding and stabilization (Vijayabaskar and Vishveshwara 2010). In the second case the features of communication paths in proteins were elucidated from PENs, and specific paths have been extensively discussed in the case of PDZ domain, which is known to bring together protein partners, mediating various cellular processes. Changes in PEN upon ligand binding, resulting in alterations of the shortest paths (energetically most favorable paths) for a small fraction of residues, indicated that allosteric communication is anisotropic in PDZ. The observations also establish that the shortest paths between functionally important sites traverse through key residues in PDZ2 domain. Furthermore, shortest paths in PENs provide us the exact pathways of communication between residues. Although the communication in PDZ has been extensively investigated, detailed information of pathways at the energy level has emerged for the first time from the present study from PEN analysis (Vijayabaskar and Vishveshwara 2010). In the third case, a set of thermophilic and mesophilic proteins were compared to determine the factors responsible for their thermal stability from a network perspective using PENs. The sub– graph parameters such as cluster population, hubs and cliques were the prominent contributing factors for thermal stability. Also, the thermophilic proteins have a better–packed hydrophobic core. The property of thermophilic protein to increase stability by increasing the connectivity but retain conformational flexibility is discussed from a cliques and communities (higher order inter–connection of residues) perspective (Vijayabaskar and Vishveshwara 2010). Finally, the remote homologues from the TIM barrel fold have been analyzed using PENs to identify the interactions responsible for the maintenance of the fold despite low sequence similarity. A study of conserved Synopsis interactions in family specific PENs reveals that the formation of the central beta barrel is vital for the TIM barrel formation. The beta barrel is being formed by either conserved long range electrostatic interactions or by tandem arrangement of low energy hydrophobic interactions. The contributions of helix–sheet and helix–helix interactions are not conserved in the families. This study suggests that the sequentially near residues forming the helix–sheet interactions are common in many folds and hence formed despite non– conservation, whereas formation of beta barrel requires long range interactions, thus more conserved within the families. The thesis also consists of an appendix in which a web–tool, developed to express proteins as networks and analyze these networks using different network parameters is discussed. The web based program–GraProStr allows us to represent proteins as structure graphs/networks by considering the amino acid residues as nodes and representing non–covalent interactions among them as edges. The different networks (classified based on edge definition) which can be obtained using GraProStr are Protein Side–chain Networks (PScNs), Cα/Cβ distance based networks (PcNs) and Protein– Ligand Networks (PLNs). The parameters which can be generated include clusters, hubs, cliques (rigid regions in proteins) and communities (group of cliques). It is also possible to differentiate the above mentioned parameters for monomers and interfaces in multimeric proteins. The well tested tool is now made available to the scientific community for the first time. GraProStr is available online and can be accessed from http://vishgraph.mbu.iisc.ernet.in/GraProStr/index.html. With a variety of structure networks, and a set of easily interpretable network parameters GraProStr can be useful is analyzing protein structures from a global paradigm (Vijayabaskar, Vidya et al. 2010). In summary, we have extensively studied DNA binding proteins using side– chain based protein structure networks and by integrating the DNA molecule into the network. Also, we have upgraded the existing methodology of generating structure networks, by representing both the geometry and the chemistry of residues as interaction energies among them. Using this energy based network we have studied diverse problems like protein structure formation, stabilization, and allosteric communication in detail. The above mentioned methodologies are a considerable advancement over existing structure network representations and have been shown in this thesis to shed more light on the structural features of proteins.

Biofilm formation is one of the most common bacterial survival strategies. Majority of bacterial species are able to form these three-dimensional structures, including pathogens like Mycobacterium tuberculosis. Representatives of Mycobacterium genus widely occur in the nature, although they can cause serious problems when they appear in medical equipment and artificial replacements of the human body. Non-pathogenic Mycobacterium smegmatis mc2 155 was used as a model organism in our experiments. We investigated morphology of the three- and six-day-old colonies (in fact biofilms) on agar and agar covered with cellophane using Stereo microscope and Scanning Electron Microscope. We found that a type of surface as well as a carbon source has a great influence on the morphology of the M. smegmatis colonies. We isolated proteomes from the agar and cellophane cultures and from planktonic culture. Two-dimensional electrophoresis was used as the main proteomic method. Proteomic data were analyzed using PDQuest software. Then the sets of proteins detected by qualitative and quantitative analyses were compared using Venn diagrams. As a result, we recognized 7 unique proteins that might be specific for recognition and adhesion of bacteria to the cellophane, no unique protein in agar proteome and 46 unique...

A steady state level of negative supercoiling is essential for chromosome condensation, initiation of replication and subsequent elongation step. DNA gyrase, found in every eubacteria, serves the essential housekeeping function of maintenance of the negative supercoiling status of the genome. The functional holoenzyme is a heterotetramer, comprising of two GyrA and two GyrB subunits. DNA gyrase is an indispensable enzyme and serves as a readily susceptible target for natural antibacterial agents. The enzymatic steps of topoisomerisation by gyrase involve transient double strand break and rejoining of the strands after intact duplex transfer. Corruption of its catalytic cycle can lead to the generation of cytotoxic double-strand DNA breaks. Most of the anti-gyrase agents achieve their objective by targeting the vulnerable step of the reaction cycle i.e. DNA cleavage step. Bacteria on their part must have evolved and adopted strategies to counter the action of external agents and prevent the generation of double strand breaks thereby safeguarding their genome. In the present thesis, attempts have been made to understand the role of three endogenous gyrase interacting proteins in gyrase modulation and cellular defense against anti-gyrase agents. The thesis is divided into six chapters. Chapter 1 introduces the wonder enzymes “DNA topoisomerases” starting with a brief classification of these enzymes and their physiological functions. In the next section, DNA gyrase has been discussed in greater detail. The structural aspects as well as the mechanism of the topoisomerisation reaction catalyzed by gyrase have been discussed. Final section gives an overview of different gyrase modulators known till date focusing on their source, structure and mode of action. The scope and objectives of the present study is presented at the end of this chapter. In Chapter 2 is aimed at understanding the physiological role of GyrI. GyrI, originally identified in Escherichia coli as an inhibitor of DNA gyrase, has been previously shown in the laboratory to render protection against gyrase poisons and also various other DNA damaging agents (mitomycin C, MNNG). Abolishing GyrI expression renders the cell hypersensitive to these cytotoxic agents. Interestingly, GyrI exhibits contrasting behavior towards two plasmid encoded proteinaceous poisons of DNA gyrase. It reduces microcin B17-mediated double-strand breaks in vivo, imparting protection to the cells against the toxin. However, a positive cooperation between GyrI and F plasmid encoded toxin CcdB, results in enhanced DNA damage and cell death. These results suggest a more complex functional interplay and physiological role for GyrI. Search for other chromosomally encoded gyrase inhibitors led to YacG, a small zinc finger protein (7.3kDa) from E. coli, shown to be a member of DNA gyrase interactome, in a protein-protein interaction network described recently. Chapter 3 deals with the detailed characterization of YacG. It is shown that YacG inhibits DNA gyrase by binding to GyrB subunit and preventing DNA binding activity of the enzyme. More importantly, it protects against the cytotoxic effects of other gyrase inhibitors like ciprofloxacin, novobiocin, microcin B17 and CcdB. Further investigations revealed that YacG and its homologues are found only in proteobacteria. Hence, it appears to be a defense strategy developed by gram-negative bacteria to fight against the gyrase targeting cytotoxic agents. Inhibition by YacG appears to be specific to E. coli gyrase as mycobacterial enzyme is refractile to YacG action. GyrB, only in gram-negative organisms, possesses extra stretch of 165 amino acids, indispensable for DNA binding. Biochemical experiments with the truncated GyrB lacking the extra stretch reveal the importance of this stretch for stable YacG-GyrB interaction. E. coli topoisomerase IV is also resistant to YacG mediated inhibition, probably due to the absence of the extra stretch in ParE subunit, which is otherwise highly similar to GyrB. Further, YacG homologues from other proteobacterial members (Sinorhizobium meliloti and Haemophilus influenzae homologues sharing 35% and 63 % identity with E. coli YacG respectively ) also inhibits E. coli DNA gyrase at comparable levels. YacG thus emerges as a proteobacteria specific inhibitor of DNA gyrase. The occurrence of both YacG and the gyrase extra stretch only in proteobacteria, suggest co-evolution of interacting partners in proteobacteria. In Chapter 4, the study of endogenous gyrase modulators is extended to Mycobacterium sp. glutamate racemase (MurI) from E. coli has been shown earlier to be an inhibitor of DNA gyrase. However, nothing much was known about its mode of action. MurI is an important enzyme in the cell wall biosynthesis pathway, which catalyses the conversion of L-glutamate to D-glutamate, an integral component of the bacterial cell wall. In this chapter, it is demonstrated that M. tuberculosis MurI inhibits DNA gyrase activity, in addition to its precursor independent racemization function. The inhibition is not species specific as E. coli gyrase is also inhibited. However, it is gyrase specific as topoisomerase I activity remains unaltered. The mechanism of inhibition by MurI has been elucidated for the first time and it is shown that MurI binds to GyrA subunit of the enzyme leading to a decrease in DNA binding of the holoenzyme. The sequestration of the gyrase by MurI results in inhibition of all reactions catalyzed by DNA gyrase. Chapter 5 is the extension of the studies on glutamate racemase into another species, i.e. Mycobacterium smegmatis. DNA gyrase inhibition seems to be an additional attribute of some of the glutamate racemases, but not all, as Glr isozyme from B. subtilis has no effect on gyrase activity in spite of sharing a high degree of similarity with the gyrase inhibitory glutamate racemases. It is shown that like the M. tuberculosis MurI, M. smegmatis enzyme is also a bifunctional enzyme. It inhibits DNA gyrase in addition to its racemization activity. Further, overexpression of the enzyme in M. smegmatis provides protection to the organism against fluoroquinolones. DNA gyrase inhibitory property thus appears to be a typical characteristic of these MurI and seems to have evolved to either modulate the function of the essential housekeeping enzyme or to provide protection to gyrase against gyrase inhibitors, which cause double strand breaks in the genome. In the above chapters, it is shown that besides its crucial role in cell wall biosynthesis, mycobacterial MurI moon lights as DNA gyrase inhibitor. That the two activities exhibited by M. tuberculosis MurI are unlinked and independent of each other is demonstrated in Chapter 6. Racemization function of MurI is not essential for its gyrase inhibitory property as mutants compromised in racemization activity retain gyrase inhibition property. MurI- DNA gyrase interaction influences gyrase activity but has no effect on racemization activity of MurI. MurI expression in mycobacterial cells provides protection against the action of ciprofloxacin, thereby suggesting a role of MurI in countering external agents targeting DNA gyrase. Further M. tuberculosis MurI overexpressed in near homologous expression system of M. smegmatis yields highly soluble enzyme which can be further used for structural and functional studies. In conclusion, the studies reveal that the endogenous inhibitors essentially influence the enzyme activity by sequestering the enzyme away from DNA. None of them cause cytotoxicity, which usually arises as a result of DNA damage caused by accumulation of gyrase-DNA covalent intermediate. On the contrary they provide protection against such gyrase poisons. Comparative analysis of these proteinaceous inhibitors, however, does not reveal a common motif or structural fold, required for their ability to inhibit DNA gyrase. Based on these studies, it can be proposed that these endogenous proteins exist to serve as cellular defense strategies against external abuse and also to modulate the intracellular activity of DNA gyrase as and when required, for accurate division, functioning and survival of the cells.

Evaluating aerodynamic noise from aircraft engines is a design stage process, so that it conform to regulations at airports. Aerodynamic noise is also a principal source of structural vibration and internal noise in short/vertical take off and landing and rocket launches. Acoustic loads may be critical for the proper functioning of electronic and mechanical components. It is imperative to have tools with capability to predict noise generation from turbulent flows. Understanding the mechanism of noise generation is essential in identifying methods for noise reduction. Lighthill (1952) and Lighthill (1954) provided the first explanation for the mechanism of aerodynamic noise generation and a procedure to estimate the radiated sound field. Many such procedures, known as acoustic analogies are used for estimating the radiated sound field in terms of the turbulent fluid flow properties. In these methods, the governing equations of the fluid flow are rearranged into two parts, the acoustic sources and the propagation terms. The noise source terms and propagation terms are different in different approaches. A good description of the turbulent flow field and the noise sources is required to understand the mechanism of noise generation. Computational aeroacoustics (CAA) tools are used to calculate the radiated far field noise. The inputs to the CAA tools are results from CFD simulations which provide details of the turbulent flow field and noise sources. Reynolds-Averaged Navier Stokes (RANS) solutions can be used as inputs to CAA tools which require only time-averaged mean quantities. The output of such tools will also be mean quantities. While complete unsteady turbulent flow details can be obtained from Direct Numerical Simulation (DNS), the computation is limited to low or moderate Reynolds number flows. Large eddy simulations (LES) provide accurate description for the dynamics of a range of large scales. Most of the kinetic energy in a turbulent flow is accounted by the large-scale structures. It is also the large-scale structures which accounts for the maximum contribution towards the radiated sound field. The results from LES can be used as an input to a suitable CAA tool to calculate the sound field. Numerical prediction of turbulent flow field, the acoustic sources and the radiated sound field is at the focus of this study. LES based on explicit filtering method is used for the simulations. The method uses a low-pass compact filter to account for the sub-grid scale effects. A one-parameter fourth-order compact filter scheme from Lele (1992) is used for this purpose. LES has been carried out for four different flow situations: (i) round jet (ii) plane jet (iii) impinging round jet and (iv) impinging plane jet. LES has been used to calculate the unsteady flow evolution of these cases and the Lighthill’s acoustic sources. A compact difference scheme proposed by Hixon & Turkel (1998) which involves only bi-diagonal matrices are used for evaluating spatial derivatives. The scheme provides similar spectral resolution as standard tridiagonal compact schemes for the first spatial derivatives. The scheme is computationally less intensive as it involves only bi-diagonal matrices. Also, the scheme employs only a two-point stencil. To calculate the radiated sound field, the Helmholtz equation is solved using the Green’s function approach, in the form of the Kirchhoff-Helmholtz integral. The integral is performed over a surface which is present entirely in the linear region and covers the volume where acoustic sources are present. The time series data of pressure and the normal component of the pressure gradient on the surface are obtained from the CFD results. The Fourier transforms of the time series of pressure and pressure gradient are then calculated and are used as input for the Kirchhoff-Helmholtz integral. The flow evolution for free jets is characterised by the growth of the instability waves in the shear layer which then rolls up into large vortices. These large vortical structures then break down into smaller ones in a cascade which are convected downstream with the flow. The rms values of the Lighthill’s acoustic sources showed that the sources are located mainly at regions immediately downstream of jet break down. This corresponds to the large scale structures at break down. The radiated sound field from free jets contains two components of noise from the large scales and from the small scales. The large structures are the dominant source for the radiated sound field. The contribution from the large structures is directional, mainly at small angles to the downstream direction. To account for the difference in jet core length, the far field SPL are calculated at points suitably shifted based on the jet core length. The peak value for the radiated sound field occurs between 30°and 35°as reported in literature. Convection of acoustic sources causes the radiated sound field to be altered due to Doppler effect. Lighthills sources along the shear layer were examined in the form of (x, t) plots and phase velocity pattern in (ω, k) plots to analyse for their convective speeds. These revealed that there is no unique convective speeds for the acoustic sources. The median convective velocity Uc of the acoustic sources in the shear layer is proportional to the jet velocity Uj at the center of the nozzle as Uc ≈ 0.6Uj. Simulations of the round jet at Mach number 0.9 were used for validating the LES approach. Five different cases of the round jet were used to understand the effect of Reynolds number and inflow perturbation on the flow, acoustic sources and the radiated sound field. Simulations were carried out for an Euler and LES at Reynolds number 3600 and 88000 at two different inflow perturbations. The LES results for the mean flow field, turbulence profiles and SPL directivity were compared with DNS of Freund (2001) and experimental data available in literature. The LES results showed that an increase in inflow forcing and higher Reynolds number caused the jet core length to reduce. The turbulent energy spectra showed that the energy content in smaller scale is higher for higher Reynolds number. LES of plane jets were carried out for two different cases, one with a co-flow and one without co-flow. LES of plane jets were carried out to understand the effect of co-flow on the sound field. The plane jets were of Mach number 0.5 and Reynolds number of 3000 based on center-line velocity excess at the nozzle. This is similar to the DNS by Stanley et al. (2002). It was identified that the co-flow leads to a reduction in turbulence levels. This was also corroborated by the turbulent energy spectrum plots. The far field radiation for the case without co-flow is higher over all angles. The contribution from the low frequencies is directional, mainly towards the downstream direction. The range of dominant convective velocities of the acoustic sources were different along shear layers and center-line. The plane jet results were also used to bring out a qualitative comparison of flow and the radiation characteristics with round jets. For the round jet, the center-line velocity decays linearly with the stream-wise distance. In the plane jet case, it is the square of the center-line velocity excess which decays linearly with the stream-wise distance. The turbulence levels at any section scales with the center-line stream-wise velocity. The decay of turbulence level is slower for the plane jet and hence the acoustic sources are present for longer distance along the downstream direction. Subsonic impinging jets are composed of four regions, the jet core, the fully developed jet, the impingement zone and the wall jet. The presence of the second region (fully developed free jet) depends on the distance of the wall from the nozzle and the length of the jet core. In impinging jets, reflection from the wall and the wall jet are additional sources of noise compared to the free jets. The results are analysed for the contribution of the different regions of the flow towards the radiated sound field. LES simulations of impinging round jets and impinging plane jet were carried out for this purpose. In addition, the results have been compared with equivalent free jets. The directivity plots showed that the SPL levels are significantly higher for the impinging jets at all angles. For free jets, a typical time scale for the acoustic sources is the ratio of the nozzle size to the jet velocity. This is ro/Uj for round jets and h/Uj for plane jets. For impinging jets, the non-dimensionlised rms of Lighthill’s source indicates that the time scale for acoustic sources is the ratio of the height of the nozzle from the wall to the jet velocity be L/Uj. LES of impinging round jets was carried out for two cases with different inflow perturbations. The jets were at Reynolds number of 88000 and Mach number of 0.9, same as the free jet cases. The impingement wall was at a distance L = 24ro from the nozzle exit. For impinging round jets, the SPL levels are found to be higher than the equivalent free jets. From the SPL levels and radiated noise spectra it was shown that the contribution from the large scale structures and its reflection from the wall is directional and at small angles to the wall normal. The difference in the range of angles where the radiation from the large scale structures were observed shows the significance of refraction of sound waves inside the flow. The rms values of the Lighthill’s sources indicate two dominant regions for the sources, just downstream of jet breakdown and in the impingement zone. The LES of impinging plane jet was done for a jet of Mach number 0.5 and Reynolds number of 6000. The impingement wall was at a distance L = 10h from the nozzle exit. The radiated sound field appears to emanate from this impingement zone. The directivity and the spectrum plots of the far field SPL indicate that there is no preferred direction of radiation from the impingement zone. The Lighthill’s sources are concentrated mainly in the impingement zone. The rms values of the sources indicate that the peak values occur in the impingement zone. The results from the different flow situations demonstrates the capability of LES with explicit filtering method in predicting the turbulent flow and radiated noise field. The method is robust and has been successfully used for moderate Reynolds number and an Euler simulation. An important feature is that LES can be used to identify acoustic sources and its convective speeds. It has been shown that the Lighthill source calculations, the calculated sound field and the observed radiation patterns agree well. An explanation for these based on the different turbulent flow structures has also been provided.

The PhD thesis is on the studsy of the influence of the ftsZ antisense RNA and FtsH protease on the synthesis and function of the Escherichia coli cytokinetic protein, FtsZ, which mediates septation during cell division. Thus, it involves three molecules, FtsZ, ftsZ antisense RNA, and FtsH protease. While the E. coli ftsZ antisense RNA is being identified and structurally and functionally characterised for the first time, there has been some earlier studies in the laboratory in which the FtsH protease was found to have influence on the presence of the FtsZ rings at the mid-cell site. The Chapter 1 is the Introduction to the thesis presented in 3 parts –Part 1A, 1B, and 1C, introducing FtsZ and bacterial cell division, bacterial antisense RNAs, and FtsH protease, respectively. The Chapter 2 gives the description of the Materials and Methods used in the study. The Chapter 3 presents the identification, structural and functional characterisation of the ftsZ cis-antisense RNA, and its role in the regulation of FtsZ protein levels. Initially, the expression of cis-encoded antisense RNA from E. coli ftsZ loci was demonstrated during the different growth phases of the bacterium (RT-PCR/qPCR data). Antisense RNA is expressed from three promoters (primer extension and promoter probe data) on the complementary strand of the ftsZ coding region and terminates at the singletrand te complementary toftsAthegenethat 3’islocatedregionupstreamof theofftsZ the gene. Induced overexpression of a portion (423 bp) of the antisense RNA, spanning the ftsZ AUG codon and the ribosome binding site of ftsZ mRNA, from pBS(KS) could downregulate the synthesis of FtsZ protein to approximately 30%, leading to cell division arrest and filamentation of the cells at 42°C. This effect was less dramatic at 30ºC, probably due to less melting of the antisense RNA. Immunostaining performed on the induced culture did not show FtsZ ring formation after overnight induction whereas reduction in the proportion of the cells carrying FtsZ rings could be clearly observed after 2 hrs of induction. Real time PCR analysis performed for relative quantitation of ftsZ mRNA and ftsZas RNA from different growth phases (0.2 to 2.5 OD600 nm) showed growth phase dependent expression of the antisense RNA. While the levels of ftsZas RNA were found to be high at lower OD cultures or early growth phase cultures, the levels were found to be low at the late log phase and stationary phase cultures. Thus, when the cells are actively dividing and therefore need more FtsZ, the levels of the ftsZas RNA are high, while the cells are not actively dividing and therefore the FtsZ levels are low, the levels of the ftsZas RNA are low. At any phase of the growth, the ratio of the ftsZ mRNA to the ftsZas RNA was always found to be 6:1. Thus, the physiological role the ftsZas RNA is to maintain the availability of the ftsZ mRNA at a level that is commensurate with the requirement for the FtsZ protein during the different stages of the cell growth and division. The Chapter 4 is on the study of the possible mechanism behind the influence of FtsH protease on the presence of FtsZ rings at the mid-cell site during septation in cell division. Immunostaining for FtsZ in the mid-log phase E. coli cells showed that 82% of the AR3289 (ftsH wild type) cells possessed FtsZ rings, while only 18% of the AR3291 (ftsH-null maintained viable by a suppressor mutation) cells showed Z-rings. While the AR3289 cells showed a cell doubling time of 20 min, the AR3291 cells had a cell doubling time of 45 min. The mass doubling time of AR3289 and AR3291 were 24 min and 54 min, respectively. These distinct differences were found in spite of the suppressor mutation suppressing all the deleterious effects of the lack of the essential protease, FtsH. Complementation of the ftsH-null cells (AR3291) with the wild type FtsH but not with the ATP-binding or ATPase, or protease-defective mutants of FtsH, restored the FtsZ ring status to about 80% of the cells. The growth rate of AR3291 was also partly restored to comparable to that of the wild type cells upon complementation. Western blotting for FtsZ, and the FtsZ-stabilising proteins, FtsA and ZipA, showed that the ftsH-null cells have low levels of FtsA, as compared to those in the isogenic wild type cells (AR3289). The levels of FtsZ and ZipA were comparable in both the cells. Quantitative PCR performed for different cell division genes within the dcw cluster showed no sign of change in the ftsA transcript levels in the ftsH-null cells, suggesting that the low levels of FtsA in the ftsH-null cells were not due to transcriptional downregulation. Further experiments showed that the half-life of FtsA protein in the AR3289 cells was 45 min, while that in the AR3291 cells was 24 min. This experiment showed that the low levels of FtsA in the ftsH-null cells was due to the low half-life of FtsA in the cells. Growth synchronisation of the AR3289 and AR3291 cells showed that the levels of FtsA prior to cell division stage do not increase in the ftsH-null cells as much as in the isogenic wild type cells. Thus, the ftsH-null cells must be somehow managing the division through the partial stabilisation of FtsZ rings by ZipA. Interestingly, immunostaining for FtsH in AR3289 cells showed the presence of FtsH at the mid-cell site, as co-localised with FtsZ, for a brief period prior to cell constriction. These observations suggest the involvement of FtsH in cell division process. The faster degradation of FtsA in the absence of FtsH protease implies that another protein, which may be a protease that directly degrades FtsA or a chaperone that helps the unfolding of FtsA for degradation, might be the substrate of FtsH protease. The absence of FtsH protease brings up the levels of this unknown protein, which in turn facilitates (if it is a chaperone) degradation of or directly degrades (if it is a protease) FtsA. This model for the link among FtsH, FtsA levels, and the presence of FtsZ has been proposed based on the observations. Thus, the present study reveals for the first time an FtsA-linked role for FtsH protease in the presence of FtsZ ring at the mid-cell site and hence in bacterial septal biogenesis. The thesis is concluded with the list of salient findings, publications, and references.