Development Of Transformation Systems For Valuable Microalgae And Functional Inference Of Hypothetical Proteins In Synechocystis Sp.PCC 6803

Haematococcus pluvialis and Crypthecodinium cohnii are valuable microalgal species.H.pluvialis is a key source of natural astaxanthin and C.cohnii has been widely used for production of Docosahexaenoic Acid(DHA).In this study,to enhance the yield of desired products and decrease production costs,we aimed to develop genetic system based on homologous recombination and electroporation.In the work,1)we determined the sensitivities of targeted algae to various antibiotics,and the results showed that the growth of H.pluvialis can be inhibited in 20 ?g/m L phosphinothric in solid/liquid medium,while the growth of C.cohnii in solid medium can be inhibited by 40 ?g/m L hygromycin B;2)we cloned the gene fragments of targeted genes by PCR.Two gene fragments were constructed by the fusion PCR,one comprised 18 S rRNA upstream fragment,resistance gene cassette and 18 S rRNA downstream fragment,the other comprised 18 S upstream fragment,resistance gene and 18 S downstream fragment;3)we optimized the electroporation conditions and performed transformation of microalgae using electroporation.The results showed that the gene fragments containing bar cassette can be integrated into H.pluvialis under the condition of 2 mm cuvette,1.2 kV voltage,25 ?F capacitor and 200 ? resistor.The integration of bar gene into the chromosome was validated by PCR analysis using genomic DNA as template.However,no transformants of C.cohnii were obtained on the hygromycin B resistant plates.Functional inference of hypothetical proteins(HPs)is a significant task in the post-genomic era,the lack of functional information hinders the deepening of research on microbial physiological genetics.We described here a network-based protocol for functional inference of HPs using experimental transcriptomic,proteomic,and protein-protein interaction(PPI)datasets.The protocol includes two steps: 1)co-expression networks were constructed using large proteomic or transcriptomic datasets of Synechocystis sp.PCC 6803 under various stress conditions,and then combined with a Synechocystis PPI network to generate bi-colored networks;2)a global algorithm was applied to the bi-colored networks for functional inference of HPs.The algorithm ranked the associations between genes/proteins with known Gene Ontology(GO)functional categories,and assumed that the top ranked HPs for each GO functional category might have a function related to the GO functional category.We applied the protocol to all HPs of the model cyanobacterium Synechocystis,and were able to assign putative functions to 122 HPs that have never been functionally characterized previously.Finally,the functional inference was validated by the known biological information of operon,and results showed that the accuracy rate of the functional inference is greater than 70%.The study provided a new protocol to integrate different types of OMICS datasets for functional inference of HPs,and could be useful in achieving new insights into the Synechocystis metabolism.