Molecular Characterization and Gene Expression Profiling of Antimicrobial Peptides in Penaeid Shrimps

The constitutive production of AMPs in shrimps ensures that animals are able to protect themselves from low-level assaults by pathogens present in the environment. As these molecules play important roles in the shrimp immune defense system, the expression level of these AMPs are possible indicators of the immune state of shrimps. The present study also indicates the antiviral property of AMPs, especially ALF, stressing the importance of their up-regulation through the application of immunostimulants/probiotics as a prophylactic strategy in aquaculture. The present study shows that shrimp defense system is equipped enough to evade WSSV infection to a certain extent, when the animals were maintained on marine yeast and probiotic diet, whereas the control diet fed group succumbed to WSSV infection. This study reveals that marine yeast and probiotic supplemented diet can delay the process of WSSV infection and confer greater protection to the animals. Particularly, the protection conferred by marine yeast, C. haemulonii S27 and Bacillus MCCB101 were highly promising imparting greater hope to the aquaculture community to overcome the prevailing disease problems in aquaculture. It may be inferred from the present study that up-regulation of AMP genes could be effected by the application of immunostimulants and probiotics. Also, AMP expression profile could be used as an effective tool for screening immunostimulants and probiotics for application in shrimp culture. Ultimately, it is likely that no single compound or strategy will provide a solution to the problem of disease within aquaculture and that, in reality, a suite of techniques will be required including the manipulation of the rearing environment, addition of probionts as a matter of routine during culture, and the use of immunostimulants and other supplements during vulnerable growth phases. Finally, the development of good management practices, the control of environmental variables, genetic improvement in the penaeid species, understanding of host-virus interaction, modulation of the shrimp immune system, supported by functional genomics and proteomics of this crustacean, as a whole suggests that the control of WSSV is not far.

Marine Actinomycetes as Source of Antimicrobial Compounds and as Probiotics and Single Cell Protein for Application in Penaeid Prawn Culture Systems

This thesis Entitled Marine actinomycetes as source of antimicrobial compounds and as probiotics and single cell protein for application in penaeid peawn culture systems. Ocean harbours more than 80% of all life on earth and remains our greatest untapped natural resource. The study revealed the potential of marine actinomycetes as a source of antimicrobial compounds. The selected streptomycetes were found to be capable of inhibiting most of the pathogenic vibrios, whichis a major problem both in hatcheries and grow out systems. The bioactive principle can be incorporated with commercial feeds and applied as medicated diet for the control of vibrios in culture systems.The hydrolytic potential inhibitory property against pathogens and non—pathogenicity to penaeid prawns make the selected Streptomycesspp.an effective probioic in aquaculture. Since there is considerably less inhibition to the natural in pond ecosystem the microbial diversityis being maintained and thereby the water quality. Actinomycetes was found to be a good source of single cell protein as an ingredient inaquaculture feed formulations. Large amount of mycelial waste (actinomycete biomassO is produced from antibiotic industries and this nutrient rich waste can be effectively used as a protein source in aquaculture feeds.This study reveals the importance of marine actinomycetes as a source of antimicrobial compounds and as a probiotic and single cell protein for aquaculture applications.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.