Mosquito-borne diseases continue to be a burden to global health. The viruses that cause these diseases are maintained in nature through a biological transmission cycle involving susceptible vertebrate and mosquito hosts. While knowledge of the interactions occurring between mosquito-borne viruses and vertebrates is considerable, much less is known about the interactions of these viruses with their disease vectors. Studies with Drosophila melanogaster have been important in understanding how insects respond to viral infections. However, mosquitoes and the viruses they vector have co-evolved during a long period of time. Unfortunately, many of the genetic advantages of a fly model are not available when working with mosquitoes. Nevertheless, a sequenced genome, and molecular tools such as high-throughput sequencing and RNAi knockdown are helping to bridge these gaps. Here we describe several additional tools for the study of virus-vector interactions in the mosquito. / Ph. D.

abstract: The fundamental building blocks for constructing complex synthetic gene networks are effective biological parts with wide dynamic range, low crosstalk, and modularity. RNA-based components are promising sources of such parts since they can provide regulation at the level of transcription and translation and their predictable base pairing properties enable large libraries to be generated through in silico design. This dissertation studies two different approaches for initiating interactions between RNA molecules to implement RNA-based components that achieve translational regulation. First, single-stranded domains known as toeholds were employed for detection of the highly prevalent foodborne pathogen norovirus. Toehold switch riboregulators activated by trigger RNAs from the norovirus RNA genome are designed, validated, and coupled with paper-based cell-free transcription-translation systems. Integration of paper-based reactions with synbody enrichment and isothermal RNA amplification enables as few as 160 copies/mL of norovirus from clinical samples to be detected in reactions that do not require sophisticated equipment and can be read directly by eye. Second, a new type of riboregulator that initiates RNA-RNA interactions through the loop portions of RNA stem-loop structures was developed. These loop-initiated RNA activators (LIRAs) provide multiple advantages compared to toehold-based riboregulators, exhibiting ultralow signal leakage in vivo, lacking any trigger RNA sequence constraints, and appending no additional residues to the output protein. Harnessing LIRAs as modular parts, logic gates that exploit loop-mediated control of mRNA folding state to implement AND and OR operations with up to three sequence-independent input RNAs were constructed. LIRA circuits can also be ported to paper-based cell-free reactions to implement portable systems with molecular computing and sensing capabilities. LIRAs can detect RNAs from a variety of different pathogens, such as HIV, Zika, dengue, yellow fever, and norovirus, and after coupling to isothermal amplification reactions, provide visible test results down to concentrations of 20 aM (12 RNA copies/µL). And the logic functionality of LIRA circuits can be used to specifically identify different HIV strains and influenza A subtypes. These findings demonstrate that toehold- and loop-mediated RNA-RNA interactions are both powerful strategies for implementing RNA-based computing systems for intracellular and diagnostic applications. / Dissertation/Thesis / Doctoral Dissertation Biochemistry 2019

Chronic lymphocytic leukemia (CLL) is a heterogeneous disease where a significant proportion of patients will develop an aggressive disease. Today, the mutational status of the immunoglobulin heavy variable (IGHV) genes is one of the strongest prognostic markers in CLL, where unmutated IGHV genes correlate with poor outcome. In addition, IGHV3-21 gene usage is associated with poor prognosis independent of mutational status. Recently, several genes were shown to be differently expressed between IGHV mutated and unmutated CLL and were suggested as prognostic markers. The aim of this thesis was to examine the applicability of these RNA-based prognostic markers in CLL. In papers I and II, the prognostic significance of LPL and TCL1A mRNA expression in CLL was investigated in 140 and 144 patients, respectively. High expression was found to be associated with inferior clinical outcome for both markers. However, CLL cases with mutated IGHV3-21 genes displayed low levels of LPL expression, indicating that LPL cannot identify this poor-risk patient group. In contrast, high TCL1A expression was detected in all IGHV3-21 cases. To elucidate the functionality of LPL in CLL, LPL lipase activity was measured in 33 cases. The lipase activity was found to be invariably low, implying an alternative function for LPL in CLL. In paper III, a comprehensive analysis of five RNA-based markers (LPL, TCL1A, ZAP70, CLLU1 and MCL1) was performed in 252 CLL patients. All RNA-based markers except MCL1 predicted clinical outcome, with LPL being the strongest. Moreover, LPL expression independently predicted overall survival when adjusted for established markers. All of the RNA-based markers added additional prognostic information to established markers, e.g. high LPL expression predicted an inferior outcome in patients with mutated IGHV genes or good-risk cytogenetics. For clinical application, over time stability of prognostic markers is crucial. In paper IV, the expression of LPL, TCL1A, ZAP70 and MCL1 was investigated in samples taken at diagnosis and at a follow-up of seven years in 104 CLL patients. LPL was found to be the most stable marker, displaying high correlation between the sequential samples, whereas ZAP70 and MCL1 varied significantly. TCL1A expression increased at follow-up, which may indicate disease progression as TCL1A promotes cell survival. In summary, this thesis highlights the applicability of RNA-based markers in CLL prognostication, both as single markers or in combination with established markers. In particular, LPL was shown to be the strongest RNA-based marker in terms of prognostic strength and stability.

The aim of this Thesis was to improve our understanding and assessment of feeding conditions for zooplanktivorous fish in the Baltic Sea. We investigated (papers I, II) the usefulness of biochemical proxies for assessments of growth and metabolic rates in the dominant Baltic copepod Acartia bifilosa. A predictive model (paper I) for egg production rate (EPR), based on body size, RNA content, and water temperature, was established using females of different geographical origin. This model demonstrates the usefulness of RNA content as a proxy for growth in zooplankton and, together with abundance data, it could be used to evaluate fish feeding conditions. Further (paper II), using A. bifilosa exposed to a food gradient, we evaluated responses of physiological rates and other biochemical proxies for growth and established correlations between physiological and biochemical variables. EPR and ingestion rate were most significantly correlated with RNA content. As assayed variables saturated at different food concentrations, food availability may affect assessments of physiological rates using proxies. In paper III, we explored the effect of high EPR and ingestion rate on astaxanthin content in A. bifilosa. We found that the astaxanthin content decreased at high feeding rates, most likely due to decreased assimilation efficiency. This may impact the quality of zooplankton as prey. The invasion of Cercopagis pengoi, a zooplanktivorous cladoceran, has altered the trophic linkages in the Baltic Sea food web. In paper IV, we evaluated the feeding of zooplanktivorous fish on C. pengoi and found that irrespective of size both herring and sprat feed on it, with large herring being more selective. In turn, C. pengoi feeds mainly on older copepods (paper V), which are acknowledged important in fish nutrition. These results indicate that C. pengoi may compete with fish due to the diet overlap. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: In progress. Paper 3: Submitted</p>

During summer, the Baltic Sea is subjected to the world’s largest cyanobacterial blooms. These blooms are linked to eutrophication and raise many questions concerning their effects on the ecosystem. To understand their impacts on the food web dynamics, it is essential to assess growth responses of grazers to these cyanobacteria. In the northern Baltic proper, copepods are the most important herbivores providing an essential link between the primary producers and higher trophic levels. In this Thesis, Papers I &amp; II evaluate methods to estimate copepod growth in response to feeding conditions in situ. The most conspicuous diazotrophic filamentous cyanobacterium in the Baltic Sea is Nodularia spumigena, a producer of nodularin which is highly toxic to vertebrates, yet its ecological role is largely unknown. In Paper III, reciprocal interactions between cyanobacteria, sympatric algae and copepods are studied. The results suggest that nodularin is likely involved in allelopathic interactions, but it is not an inducible defense against grazers. Furthermore, the results of Papers IV &amp; V, indicate that natural assemblages of N. spumigena and Anabaena spp. may support copepod reproduction and that total diazotrophic filamentous cyanobacteria appear to provide a beneficial feeding environment for the feeding stages of copepod nauplii, most probably by stimulating the microbial communities that nauplii feed upon. Since cyanobacterial blooms are projected to increase due to global climate change, the combined effects of toxic cyanobacteria, ocean acidification and global warming predicted for year 2100 are further investigated on copepods in Paper IV. Taken together, these studies indicate that filamentous diazotrophic cyanobacteria contribute to sustaining secondary productivity and have potential implications of management practices with respect to combating eutrophication, global climate change and sustaining fish feeding conditions. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: Manuscript. Paper 5: Manuscript.</p>

The clinical course of chronic lymphocytic leukemia (CLL) is highly heterogeneous, which has prompted the search for biomarkers that can predict prognosis in this disease. The IGHV gene mutation status and certain genomic aberrations have been identified as reliable prognostic markers of clinical outcome for this disorder. However, the search for more feasible prognostic markers in CLL is still being pursued. Recently, certain single nucleotide polymorphisms (SNPs) in the GNAS1, BCL2 and MDM2 genes and the RNA expression levels of the LPL, ZAP70, TCL1, CLLU1 and MCL1 genes were suggested as novel prognostic markers in CLL. In papers I-III, we performed genotyping analyses of the GNAS1 T393C, BCL2 -938C&gt;A and MDM2 SNP309 polymorphisms in 268-418 CLL patients and related the genotypes with clinical data. Association studies between the polymorphisms and established prognostic markers (i.e. IGHV mutation status, genomic aberrations, CD38 expression) were also performed. Our studies did not find any significant relationship between these SNPs with either clinical outcome or other known prognostic markers in CLL. In paper IV, we measured the RNA expression levels of LPL, ZAP70, TCL1, CLLU1 and MCL1 in 252 CLL cases and correlated these levels with clinical outcome. Here, we verified that high expression of all these RNA-based markers, except MCL1, were associated with an unfavourable prognosis. We also confirmed a close relationship between IGHV mutation status and the RNA-based markers, especially for LPL and CLLU1 expression. Among the RNA-based markers, multivariate analysis revealed LPL expression as the strongest independent prognostic marker for overall survival and time to treatment. Furthermore, the RNA-based markers could add further prognostic information to established markers in subgroups of patients, with LPL expression status giving the most significant results. In summary, data from papers I-III could not verify the GNAS1 T393C, BCL2 -938C&gt;A and MDM2 SNP309 polymorphisms as prognostic markers in CLL. Future SNP markers must hence be confirmed in large, independent cohorts before being proposed as prognostic marker in CLL. In paper IV, we conclude that LPL expression appears to be the strongest among the RNA-based markers for CLL prognostication. Further efforts to standardize LPL quantification are required before it can be applied in the clinical laboratory to predict clinical outcome in this disease.

No description available.

The Transcription Start Site Associated non-coding RNAs (TSSaRNAs) have been predicted across the three domain of life. However, still, there are no reliable annotation efforts to identify their biological functions and their underline molecular machinery. Therefore, this project addresses the question of what are the potential functions of TSSaRNAs regarding their roles in addressing the cellular functions. To answer this question, we aimed to accurately identify TSSaRNAs in the model organism Halobacterium salinarum NRC-1 (an Archean microorganism) that incubated at the standard growth condition. Consequently, we aimed to investigate TSSaRNAs structural stability in the term of the thermodynamic energies. Moreover, we attempted to functionally annotate TSSaRNAs based on Rfam functional classification of non-coding RNAs. Based on the statistical approach we developed an algorithm to predict TSSaRNA using next-generation RNA sequencing data (RNA-Seq). To perform structural annotation of TSSaRNAs, we investigated the structural stability of TSSaRNAs by modeling the secondary structures by minimizing the thermodynamic free energy. We simulated TSSaRNAs tertiary structures based on the secondary structures constrain using the Rosetta-Common RNA tool. The structures of the minimum free energy supposed to be biophysically stable structures. To investigate the higher order structures of TSSaRNAs, we studied the hybridization between TSSaRNAs and their cognate genes as part of RNA based regulation system. Also, based on our hypothesis that TSSaRNAs may bind to protein to trigger their function, we have investigated the interaction between TSSaRNAs and Lsm protein which known as a chaperone protein that mediates RNA function and involved in RNA processing. Our pipeline to perform the functional annotation of TSSaRNAs aimed to classify TSSaRNAs into their corresponding Rfam families based on two steps: either through querying TSSaRNAs sequences against the co-variance models of Rfam families or by querying the Rfam sequences against the co-variance models of the consensus secondary structures in TSSaRNAs. The results showed that the prediction algorithm has succeeded to identify a total of 224 TSSaRNAs that expressed in the same strand of the mRNAs and 58 TSSaRNAs that expressed as antisense of the mRNAs. The identified TSSaRNAs molecules showed a median length of 25 nucleotides. Regarding the structural annotation of TSSaRNAs, the results showed that most of TSSaRNAs possessed thermodynamically stable secondary structures and their tertiary structures were capable of forming more complex structures through binding with other biomolecules. About the formation of higher-order structures, we have observed that most of TSSaRNAs (92.2%) were capable of hybridizing into their cognate genes also 55 TSSaRNAs indicated putative interactions with Lsm protein. Furthermore, the computation docking experiments demonstrated the TSSaRNAs-Lsm complexes associated with favorable binding energy of a median of -542900 kcal mole -¹. Regarding the functional annotation of TSSaRNAs, the results showed that the majority of TSSaRNAs (42.05%) considered as potential cis-acting regulators such as cis-regulatory element and sRNAs, but still, there are potential trans-acting regulators to regulate distant molecules such as CRISPR and antisense RNA. Moreover, the results indicated that TSSaRNAs could trigger more complex function as a catalytic function such as Riboswitch or to play a role in the defense against a virus such as CRISPR. As a conclusion; based on the results of this study we could state that TSSaRNAs have several potential functions opening the experimental validation perspective. / Os RNA não codificantes associados ao sítio de início da transcrição - em inglês, transcription start site associated non-coding RNAs (TSSaRNA) - foram observados nos três domínios da vida. No entanto, sem esforço confiável de anotação para identificar suas funções biológicas e seus mecanismos moleculares. Portanto, esse projeto levanta a questão de quais são as funções em potencial dos TSSaRNAs a respeito de seus papeis nas funções celulares. Para responder esta questão, nós objetivamos em identificar de forma eficaz os TSSaRNAs no organismo modelo Halobacterium salinarum NRC-1 (um microrganismo do domínio Arqueia) encubado em uma condição de crescimento padrão. Consequentemente, nós investigamos a estabilidade estrutural dos TSSaRNAs em relação a energias termodinâmicas. Ainda, fizemos a anotação funcional dos TSSaRNAs baseado na classificação funcional Rfam dos RNAs não-codificantes. Baseada em uma abordagem estatística nós desenvolvemos um algoritmo para predizer TSSaRNA usando dados de sequenciamento de RNA de nova geração (RNA-Seq). Para investigar a estabilidade estrutural dos TSSaRNAs nós modelamos as estruturas secundárias minimizando a energia livre termodinâmica para alcançar a estrutura mais estável biofisicamente. Nós simulamos estruturas terciárias de TSSaRNAs baseado nas restrições das estruturas secundárias usando a ferramenta Rosetta-Common RNA. As estruturas de energia livre mínima seriam supostamente estruturas estáveis biofisicamente. Para investigar as estruturas de ordem superior (quaternária) dos TSSaRNAs, nós estudamos a hibridização entre os TSSaRNAs e seus genes cognatos como parte de um possível sistema de regulação baseado em RNA. Ainda, baseada na hipótese que os TSSaRNAs podem ligar à proteína para habilitar sua função, nós investigamos a interação entre TSSaRNAs e proteína Lsm que é conhecida por ser uma proteína chaperone que media função do RNA e está envolvida no processamento do RNA. Nosso pipeline para executar a anotação funcional dos TSSaRNAs objetivou classificar as TSSaRNAs em suas correspondentes classes Rfam baseado em dois passos: por meio de consulta das sequências TSSaRNA em relação a modelos de covariância de famílias Rfam ou por consulta de sequências Rfam em relação a modelos de covariância das estruturas de secundárias de consenso das estruturas secundárias nos TSSaRNAs. Os resultados mostraram que o algoritmo de detecção teve sucesso em identificar um total de 224 TSSaRNAs que expressaram na mesma direção dos mRNAs e 58 TSSaRNAs que expressaram no sentido oposto (antisenso) dos mRNAs. As moléculas TSSaRNAs identificadas mostraram um comprimento mediano de 25 nucleotídeos. A respeito da anotação estrutural dos TSSaRNAs, os resultados mostraram que a maioria dos TSSaRNAs possuíam estruturas secundárias estáveis termodinamicamente e suas estruturas terciárias foram capazes de formar estruturas mais complexas por meio de vínculos com outras biomoléculas. Quanto à formação de estruturas de maior de estruturas de alta ordem nos observamos que a maioria dos TSSaRNAs (92.2%) são capazes, pelo menos em princípio, de hibridizar em seus genes cognatos e, também, 55 TSSaRNAs evidenciaram interagir com a proteína Lsm. Além disso, os experimentos computacionais de docking demonstratam os complexos TSSaRNAs-Lsm associados com energia de ligação favorável com uma média de - 542900 kcal mole -¹. Quanto à anotação funcional dos TSSaRNAs, os resultados mostraram que a maioria dos TSSaRNAs (42.05%) podem ser consideradas potenciais reguladores atuando em cis tais como elemento cis-regulamentar e sRNAs, mas ainda há pontenciais reguladores atuando em trans para regular moléculas em loci distantes, tais como CRISPR e RNA antisense. Além disso, os resultados mostraram que TSSaRNAs podem potencialmente ativar funções mais complexas como uma função catalítica, tal como Riboswitch ou executar um papel de defesa contra vírus, tal como CRISPR. Como conclusão; baseado nos resultados desse estudo, nós podemos afirmar que TSSaRNAs possuem várias funções em potencial abrindo a perspecitiva de validação experimental.